Detection of transgenic and endogenous plant DNA in blood and organs of Nile tilapia, Oreochromis niloticus fed a diet formulated with genetically modified soybean meal

Anxiety regarding the fate of ingested transgenic DNA in farmed fish fed genetically modified (GM) soybean meal (SBM) has been raised with regard to human consumption. The objective of this study was to detect possibility of gene transfer of transgenic and endogenous DNA fragments in Nile tilapia (Oreochromis niloticus) blood and organs after consumption of a GM SBM diet. Nile tilapias with an average weight of 75.0 g were fed diets containing 48% GM or non-GM SBM for 21 days. During this period, a GM SBM diet was fed to fish for 12 days, and then switched to feed with non-GM SBM for 9 days for determining the residual span of the transferred cauliflower mosaic virus (CaMV) 35S promoter fragment. Blood, spleen, liver, intestine, kidney, and muscle tissues were taken (n = 10) every three days during the feeding period. Total DNA was extracted from the samples and analyzed by polymerase chain reaction (PCR) for determining the presence of a 108-bp fragment of the CaMV 35S promoter and a 144-bp fragment of the soybean chloroplast-specific DNA. Low-copy chloroplast-specific DNA fragment was detected in all organ and tissue samples and the majority of intestinal samples of fish fed GM SBM diet. Similarly, a low number and faint signals of the CaMV 35S promoter fragments were detected in all organ samples except muscle of fish fed the GM SBM diet, while none were detected 3 days after changing to a non-GM SBM diet. A very low frequency of transmittance to muscle and organs of fish was confirmed. It is recognized that the low copy number of transgenic DNA in the GM SBM diet is a challenge to their detection in tissues. These results suggested that transgenic DNA would be processed in the gastrointestinal tract in a similar manner with conventional plant DNA

ANALISIS PENGARUH PENDAPATAN ASLI DAERAH, TINGKAT INVESTASI DAN TENAGA KERJA TERHADAP PDRB JAWA TENGAH

PDRB didefinisikan sebagai jumlah nilai tambah yang dihasilkan oleh seluruh unit usaha dalam suatu wilayah, atau merupakan jumlah seluruh nilai barang dan jasa akhir yang dihasilkan oleh seluruh unit ekonomi di suatu wilayah. Dimana Tingkat PDRB dapat menggambarkan pertumbuhan Ekonimi suatu wilayah. Tingginya tingkat pertumbuhan ekonomi yang ditunjukkan dengan tingginya nilai PDRB menunjukkan bahwa daerah tersebut mengalami kemajuan dalam perekonomian. Propinsi Jawa Tengah adalah propinsi yg memeliki PDRB paling rendah di pulau jawa dibandingkan propinsi-propinsi yg lain dimana secara dominan sumber penerimaan PDRB jawa tengah dipengaruhi oleh 3 faktor yaitu PAD, Tingkat Investasi, dan Tenaga kerja maka dari itu Tujuan dari penelitian ini adalah untuk mengetahui seberapa besar pengaruh PAD, Tingkat Investasi, dan Tenga Kerja terhadap PDRB di Jawa Tengah. Metode Penelitian menggunakan Analisis regresi berganda dengan menggunakan data rentang waktu 15 tahun mulai tahun 1994 hingga 2008. Hasil analisa data menunjukkan bahwa model penelitian ini lolos uji asumsi klasik dengan R-square model sebesar 0,958. PAD, Tingkat Investasi, Tenaga kerja berpengaruh positif dan signifikan secara parsial maupun simultan terhadap PDRB Jawa tengah. Koefisien PAD sebesar 0,812. Adanya pengaruh yg positif antara Tingkat Investasi dengan PDRB Jawa Tengah berdasarkan hasil regresi dapat dilihat koefisien tingkat investasi 0,036.Adanya pengaruh yg positif antara Tenaga Kerja dengan PDRB Jawa Tengah berdasarkan hasil regresi dapat dilihat koefisien 0,924 Tenaga Kerja. Kata kunci : PDRB, PAD, Tingkat Investasi, Tenaga Kerj

ANALISIS PENETAPAN SATUAN WILAYAH PEMBANGUNAN DI KABUPTEN TEGAL

Nowadays, the developments of autonomous areas are expected to be the solution of areal defect, through the implementations local development policies. The defect might be the result of the potential differences among each area, the public service facility differences, or the lack of coordination in development practices. In the struggle of the areal building, concept of Development Areal Unit is the most appropriate to be applied. Furthermore, the fulfillment of Development Areal Unit can be used as a tool for government to make it easier in coordinating the executions of local development. There are several aims of this research. The first, to find out the economical potencies that can be grown in each subdistrict in Tegal Regency; the second, to to find out the interactional strength among the districts, the third, to find out about which subdistricts that can be fulfilled based on the local potencies, and the fourth is to find out the interactional strength between districts and the centre of the growth. Location Quotient, Gravitation and Scalogram analyses within the data including regency’s PDRB, subdistricts’ PDRB, PDRB per-capita in each district, population quantities, distances among the district’s capital, and the quantities and types of service facilities available in each subdistrict in Tegal Regency. The result of the analysis showed that there were 4 Development Area Unit that is identified in Tegal Regency. They were SWP I, including Slawi, Dukuhturi, Talang, Tarub, Adiwerna, Pangkah, Dukuhwaru, Lebaksiu, Jatinegara, and Kedungbanteng subdistricts; meanwhile, SWP II, including Kramat, Wrureja, and Suradadi subdictricts. SWP III, including SWP Margasari, Pagerbarang, and Balapulang subdistricts; and SWP IV, including Bumijawa and Bojong subdistricts

Stochastic Block Transition Models for Dynamic Networks

There has been great interest in recent years on statistical models for dynamic networks. In this paper, I propose a stochastic block transition model (SBTM) for dynamic networks that is inspired by the well-known stochastic block model (SBM) for static networks and previous dynamic extensions of the SBM. Unlike most existing dynamic network models, it does not make a hidden Markov assumption on the edge-level dynamics, allowing the presence or absence of edges to directly influence future edge probabilities while retaining the interpretability of the SBM. I derive an approximate inference procedure for the SBTM and demonstrate that it is significantly better at reproducing durations of edges in real social network data.Comment: To appear in proceedings of AISTATS 201

Cholesterol and Malondialdehyde Contents of Broiler-Chicken Meat Supplemented with Indigofera Zolingeriana Top Leaf Meal

This research aimed to increase functional value of broiler-chicken meat containing high antioxidant and low cholesterol through substitution of soybean meal (SBM) with Indigofera zollingeriana top leaf meal (ILM). The experiment used 160 day old broiler chicken (Cobb strain). The experimental chicken were provided dietary treatments when they were 15-days old (initial body weight of 460.5±1.56 g/bird) and terminated on day 35. A completely randomized design (CRD) with four treatments and four replications and ten birds in each replication was used in this experiment. Dietary treatments were: R1= diet containing 20% soybean meal (SBM) without I. zollingeriana top leaf meal (ILM); R2= diet containing 16% SBM and 5.9% ILM; R3= diet containing 12% SBM and 11.8% ILM; R4= diet containing 8% SBM and 17.74% ILM. Variables measured were performances (feed consumption, body weight gain, and feed conversion) and the quality of broiler meat (cholesterol, fat content, and malondialdehyde [MDA] concentration). The results showed that supplementation of 17.74% ILM (R4) as the substitution of 60% soybean meal protein produced the same performances of broilers as those of control diet (R1). Supplementation of 11.8% ILM as the substitution of 40% soybean meal protein (R3) decreased meat cholesterol by 34.70%, meat fat content by 52.93%, and MDA concentration by 62.52%. The conclusion of this study was that supplementation of 17.74% ILM produced the same performances as that of control diet, increased antioxidant content of the meat, indicated by a lower MDA concentration, and decreased cholesterol, as well as fat content of broiler-chicken meat

Variational Inference for Stochastic Block Models from Sampled Data

This paper deals with non-observed dyads during the sampling of a network and consecutive issues in the inference of the Stochastic Block Model (SBM). We review sampling designs and recover Missing At Random (MAR) and Not Missing At Random (NMAR) conditions for the SBM. We introduce variants of the variational EM algorithm for inferring the SBM under various sampling designs (MAR and NMAR) all available as an R package. Model selection criteria based on Integrated Classification Likelihood are derived for selecting both the number of blocks and the sampling design. We investigate the accuracy and the range of applicability of these algorithms with simulations. We explore two real-world networks from ethnology (seed circulation network) and biology (protein-protein interaction network), where the interpretations considerably depends on the sampling designs considered