Manajemen Program Siaran Lokal Aceh TV Dalam Upaya Penyebarluasan Syariat Islam Dan Pelestarian Budaya Lokal

Managing broadcasting management is not easy. Managing the broadcasting business is a difficult and challenging. This research aims to analyze the activity of management and organizational performance ACEH TV television media in an effort to disseminate the Islamic Sharia and Preservation of Local Culture in Aceh. This research is descriptive qualitative. Informants of this research is managing director, program director, executive producer, cameraman / reporter, as well as additional informants Regional Chairman of the Indonesian Broadcasting Commission (KPID) Aceh, Aceh Province Department of Islamic Law, and local media observers. The location of this research is in Banda Aceh, Aceh province. Sampling was done purposively. Data collected through observation, interviews, and documentation. Data were analyzed by analysis of an interactive model of Miles and Huberman. The results showed that the ACEH TV as the medium of television that is broadcasting management ACEH have done according to a local television broadcasting standard. Agenda setting function of mass media performed in the ACEH TV dissemination of Islamic Shariah in Aceh and local culture to influence the people of Aceh to implement Islamic Sharia and also maintain the culture and local wisdom Aceh. It can be seen from all the programs that are aired ACEH TV is a program of local cultural nuances of Islamic law. There are still some shortcomings in running broadcasting broadcasting technology such as lack of equipment that is increasingly sophisticated. The results of image editing is very simple, and some programs presenter still looks stiff when in front of the camera

Comparison of methylation level estimates for the bisulfite sequencing, HumanMethylation 450K and MeDIP-seq data.

<p>Data are shown for the 28 islands (associated with 36 genes) containing CpG sites that overlapped with those interrogated by HumanMethylation 450K array for sample GM01240. Evolutionary strata information is shown to the right of the ideogram of the human X chromosome <a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0050233#pone.0050233-Ross1" target="_blank">[66]</a>: the blue line represents the S3 stratum; the purple line represents the S2 stratum and the red line the S1 stratum. Both names are given for genes sharing a CpG island separated by “/”. Methylation level estimates for each of the techniques are shown to the right of the gene names in light green (low), green (medium), and dark green (high). Examples of four genes are shown in more detail on the right of the figure. The gene names are highlighted in colour at the top of each panel and in a corresponding colour on the gene list. Data for the bisulfite sequencing (BS-s), HumanMethylation 450K (450K) and MeDIP-seq (MD-s) are shown at the top, center and bottom of each panel, respectively. The genes shown give examples where the three techniques agree in methylation level: low level methylation in the gene ZFX, medium level methylation in the PRPS2 gene, and a high level of methylation in the ACRC gene. Data are also given for the HCFC1/TMEM187 genes, for which different methods show inconsistency in the classified methylation levels. See <a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0050233#pone.0050233.s004" target="_blank">Figure S4</a> for data for sample GM01247.</p

Concordance of the HumanMethylation 450K (450K) and MeDIP-seq (MD-s) data with bisulfite sequencing (BS-s) data.

<p>The top part of the table gives the concordance of the average beta-values for the 326 probes on the X chromosome from the HumanMethylation 450K (450K) and the methylation score calculated by the MEDIPS software for the MeDIP-seq data (MD-s) to the methylation levels for the bisulfite data (BS-s) from MethTools. The second half of the table contains the concordance for a similar analysis for the HumanMethylation 450K and MeDIP-seq data for all autosomal chromosomes.</p

Coverage by MeDIP-seq and the HumanMethylation 450K BeadChip of different genomic features.

<p>The different features are described along the bottom axis. 100% coverage is defined as covering all of the elements of a particular type in the human genome. Coverage for MeDIP-seq data (MD-s) (averaged for GM01240 and GM01247) is shown as blue bars and for the HumanMethylation 450K (450K) as red bars. Average percentages covered for each technique for each group of features are given above the bar chart. For MeDIP-seq the region or feature was defined as being covered if any part of the region or feature was covered by or overlapped any part of one or more sequencing reads. The coverage for the MeDIP-seq was consistent between the two samples (see <a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0050233#pone.0050233.s005" target="_blank">Table S1</a>), illustrating a high degree of reproducibility for the technique. The coverage shown for the HumanMethylation 450K is reported as the number of features where at least one probe present on the array mapped within the features under consideration i.e. is based on the array design.</p

Leveraging osteoclast genetic regulatory data to identify genes with a role in osteoarthritis.

There has been growing interest in the role of the subchondral bone and its resident osteoclasts in the progression of osteoarthritis (OA). A recent genome-wide association study (GWAS) identified 100 independent association signals for OA traits. Most of these signals are led by non-coding variants, suggesting genetic regulatory effects may drive many of the associations. We have generated a unique human osteoclast-like cell-specific expression quantitative trait locus (eQTL) resource for study of the genetics of bone disease. Considering the potential role of osteoclasts in the pathogenesis of OA, we performed an integrative analysis of this dataset with the recently published OA GWAS results. Summary-data-based Mendelian Randomisation (SMR) and co-localisation analyses identified 38 genes with a potential role in OA, including some that have been implicated in Mendelian diseases with joint/skeletal abnormalities, such as BICRA, EIF6, CHST3 and FBN2. Several OA GWAS signals demonstrated co-localisation with more than one eQTL peak, including at 19q13.32 (hip OA with BCAM, PRKD2 and BICRA eQTL). We also identified a number of eQTL signals co-localising with more than one OA trait, including FAM53A, GCAT, HMGN1, MGAT4A, RRP7BP and TRIOBP. SMR analysis identified 3 loci with evidence of pleiotropic effects on OA-risk and gene expression: LINC01481, CPNE1 and EIF6. Both CPNE1 and EIF6 are located at 20q11.22, a locus harbouring two other strong OA candidate genes, GDF5 and UQCC1, suggesting the presence of an OA-risk gene cluster. In summary, we have used our osteoclast-specific eQTL dataset to identify genes potentially involved with the pathogenesis of OA.</p

Participant characteristics (Replication Study).

<p>Values are means ± standard deviation for each quantitative trait.</p

Replicated meQTL hits.

<p>a) ID of probe set on DMH array,</p><p>b) chromosome.</p><p>c) genomic coordinates of probe set in build37.</p><p>d) genomic coordinates of SNP in build37.</p><p>e) coefficient of SNP effect.</p><p>f) standard error for the SNP effect.</p><p>g) p-value for the SNP effect.</p><p>h) ID of probe on Illumina 27k array,</p><p>i) genomic coordinates of CpG probed in build37.</p><p>j) one-sided p-value for the SNP effect in the direction of the original association.</p

Extracorporeal shockwave therapy improves functional outcomes of adhesive capsulitis of the shoulder in patients with diabetes

Adhesive capsulitis of the shoulder (ACS) is the most prevalent musculoskeletal disorder of the upper extremity (1,2) among people with diabetes. ACS is characterized by intense shoulder pain with progressive limitation of joint mobility and functional disability, negative impact on the quality of life, and increased health care costs (3)

Flowchart showing the analysis pipeline.

<p><b>Top:</b> Association of DMH Methylation Score with phenotypes. <b>Bottom:</b> Primary <i>cis</i>-meQTL association study, followed by replication study. <b>Left:</b> Association of DMH probe sets with significant meQTLs with mRNA expression. <b>Right:</b> Text mining of meQTLs significant in the primary study.</p

Boxplots showing methylation level plotted against genotype for the 5 replicated meQTLs in both the primary study (left panels) and replication study (right panels).

<p>All SNPs passed quality control filtering and association with methylation levels in both data sets.</p