Judul: Excretory/secretory antigen of ascaridia galli L3 stage to trigger yolk immunoglobulin in laying hens
Abstrak: Ascaridiosis caused by the nematode Ascaridia galli. A study was carried out to characterize excretory/secretory antigen of A. galli from larval stage to trigger anti-ascaridiosis yolk immunoglobulin in laying hens. A. galli L3 were recovered from intestines of 100 heads chickens 7 days after oesophagus inoculation with 6000 L2. L3 recovered in this manner were cultured (5 – 10 ml-1) in flasks containing rosswell park memorial institute (RPMI) 1640 media, pH 6.8, without phenol red. Cultures were incubated at 370C in 5% CO2 and culture fluid was collected after 3 days in culture. To prepare excretory/secretory antigen, culture medium were concentrated with vivaspin 30.000 MWCO, and antigen protein concentration were counted as described in Bradford method. The molecular weight of excretory/secretory antigen was determined with sodium dodecyl sulphate polyacrylamide gel electrophoresis (SDS PAGE). Active immunizations were applied intra muscularly of chickens with an initial dose of 80 μg. The immunizations were repeated three times with dose of each 60 μg with an interval of one week. The first immunizations were excretory/secretory antigen mixed with fruend adjuvant complete and subsequently mixed with freund adjuvant incomplete. The chicken’s eggs were collected from 49 day after immunizations. Anti-ascaridiosis yolk immunoglobulin (IgY) was extracted from egg yolks by means of ammonium sulphate and purified using fast performance liquid chromatography (FPLC). The purity of anti-ascaridiosis IgY was determined by Bradford method (λ = 280 nm). Antibody was detected by agar gel precipitation test (AGPT) and enzyme linked immunosorbant assay (ELISA). Antigen were detected with immunohistochemistry. Chickens were challanged with dose of 1000 L2 A. galli. Passive immunizations were applied ten times with dose of each 0,875 mg IgY with an interval of one day intra orally. IgY anti-ascaridiosis was tested against A. galli survival in vitro.
Keyword: Unggas, Isolasi dan karakterisasi antigen, Purifikasi imunoglobulin yolk, Pengukuran antibodi ayam petelur, Metode Imunohistokimia, Ascaridiosis

Judul: Deteksi Imunoglobulin Y Pada Telur Asin Anti Diare Dan Flu Burung Dengan Metode Agar Gel Precipitation Test (AGPT) Dan Hemagglutination Inhibition Test (Hi Test)
Abstrak: This study was conducted to detect specific IgY (anti Enteropathogenic Escherichia coli (EPEC), anti Salmonella Enteritidis, and anti Avian Influenza Virus H5N1) in salted egg. The laying hens were vaccinated with EPEC and Salmonella Enteritidis inactive-vaccine and AI H5N1 vaccine (IPB-Shigeta). Nine eggs were salted by NaCl solution (1:2). The eggs were salted by three times of long-term salting (10 days, 15 days, and 20 days). The IgY was detected using AGPT and haemagglutination inhibition (HI) test. The AGPT result showed that specific IgY of EPEC and Salmonella Enteritidis detected at 10 days and 15 days long-term salting. The mean titer of anti AI-IgY (over 24) was detected using by HI at all long-term salting. In conclusion, salted egg yolk still have specific IgY which is potential for production functional salted egg.
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Judul: Real Option Valuation Using Binomial Decision Trees.
Abstrak: A firm that decides to invest has a choice to invest in real assets. A method which is usually used in valuation of the project is discounted cash flow (DCF) method. But, this method can’t be used in projects that account for value of managerial flexibility, such as decision to suspend operations temporarily. Therefore, this kind of project needs to be assessed using real option. Real option valuation can be done in some ways, including the use of path-dependent simulation, as well as closed-form models like Black-Scholes model, partial differential equation, and binomial or multinomial approaches. In this paper, real option valuation using binomial decisions id discussed. Determination of the project value can be done in three steps. First, calculate the expected present value of the project. Next, calculate volatility of the project using Monte Carlo simulation. Last, construct a binomial tree to model the dynamics of the project value using the parameters of the stochastic process, and then add some decision nodes to model the project’s real options.
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