Judul: Antibiotic resistance patterns of Pasteurella multocida (Type B) isolated from Cattle in Indonesia
Abstrak: Septicemia hemoragik adalah penyakit pasteurelosis akut, sangat fatal pada sapi, kerbau, domba dan kambing yang menyebabkan kerugian ekonomi yang serius di daerah tropis dan subtropis di Asia dan Afrika. Serotipe Pasteurella multocida yang bertanggung jawab atas penyakit yang ditemukan di Asia adalah serotipe B:2 sedangkan di Afrika adalah serotipe E:2. Untuk mengobati infeksi bakteri, antibakteri atau antibiotik boleh digunakan. Namun, karena penggunaan antibiotik yang terus menerus, banyak strain P. multocida dan spesies bakteri lainnya yang resisten telah muncul. Penelitian ini dilakukan untuk mengetahui efektivitas berbagai antibiotik yang meliputi bacitracin, vancomycin, oxytetracycline, enrofloxacin, gentamicin, ampicillin, dan erythromycin terhadap Pasteurella multocida yang diisolasi dari sapi yang diduga menderita septikemia hemoragik di Indonesia. Sensitivitas antibiotik dengan antibiotik yang berbeda diperiksa dengan metode difusi disk dan ditemukan resisten terhadap bacitracin, vankomisin, ampisilin, dan eritromisin. Meskipun P. multocida cukup sensitif terhadap oksitetrasiklin, disimpulkan bahwa enrofloksasin dan gentamisin adalah antibiotik yang paling efektif yang dapat digunakan dalam pengobatan septikemia hemoragik karena sensitivitasnya yang tinggi.
Keyword: Pasteurella multocida, resistensi antibiotic, septicemia hemoragik

Judul: Keragaman Fenotipik dan Molekuler Pasteurella multocida dari Beberapa Wilayah di Indonesia
Abstrak: Pasteurella multocida adalah bakteri Gram-negatif penyebab septicemia epizootica (SE) pada kerbau dan sapi yang tergolong ke dalam penyakit hewan menular strategis (PHMS) dan masih menjadi masalah serius dalam dunia peternakan Indonesia. Bakteri ini memiliki keragaman yang sejauh ini lazim dideteksi melalui serotyping berdasarkan sifat antigenik polisakarida kapsul. Alternatif untuk menganalisis keragaman hayati adalah dengan menggunakan sodium dodecyl sulphate polyacrylamide gel electrophoresis (SDS-PAGE) dan random amplified polymorphic DNA (RAPD). Penelitian ini dilakukan untuk mengetahui keragaman hayati P. multocida dari beberapa wilayah di Indonesia berdasarkan karakter fenotipe, profil protein, dan pola pita RAPD. Identifikasi bakteri dilakukan secara biokimia dengan menggunakan sistem identifikasi tradisional dan API® 20NE yang selanjutnya dikonfirmasi secara molekuler menggunakan polymerase chain reaction (PCR). Ekstraksi protein bakteri dilakukan dengan teknik freeze-thawing dan ekstraksi DNA dilakukan dengan menggunakan reagen DNAzol®. Elektroforesis protein dan RAPD masing-masing dilakukan pada gel poliakrilamida 12% dan gel agarose 1,5%. Hasil penelitian menunjukkan P. multocida dari beberapa wilayah di Indonesia memiliki rentang berat molekul pita protein 12–209 kDa. Rentang fragmen RAPD P. multocida berkisar antara 307–3100 bp. Secara fenotipik, P. multocida dari Provinsi Sulawesi Selatan memiliki keragaman karakter pertumbuhan di media agar MacConkey. Berdasarkan analisis hierarchical clustering terhadap pola pita RAPD dan profil protein sel utuh, masing-masing terbentuk empat dan lima klaster yang menunjukkan keragaman molekuler P. multocida yang diisolasi dari beberapa wilayah di Indonesia. Keragaman molekuler juga teramati berdasarkan hasil pengurutan gen ompH yang mengelompokkan isolat-isolat P. multocida yang digunakan dalam penelitian ini ke dalam lima klaster., Pasteurella multocida is a Gram-negative bacteria that causes septicemia epizootica (SE) in buffaloes and cattle and the disease itself causes serious problems in the Indonesian livestock and is classified as a strategic transmissible animal disease. The diversity of these bacteria so far has been detected using the serotyping method based on the antigenic properties of the capsule polysaccharides. The alternative for analyzing its diversity is to use sodium dodecyl sulphate polyacrylamide gel electrophoresis (SDS-PAGE) dan random amplified polymorphic DNA (RAPD). This study was conducted to determine P. multocida diversity from several regions in Indonesia based on its phenotypic character, protein profile, and band pattern of RAPD. Bacterial identification was carried out biochemically using traditional identification and API® 20NE systems and then confirmed molecularly using polymerase chain reaction (PCR). The freeze-thawing technique was performed to obtain the bacterial protein extract. The extracted protein and RAPD product were then electrophoresed on 12% polyacrylamide gel and 1.5% agarose gel, respectively. The results showed that the molecular weight range of the protein bands is 12–209 kDa and the band pattern of RAPD is ranged from 307–3,100 bp. Phenotypically, P. multocida from South Sulawesi Province had a variety of growth characters in MacConkey agar media. Based on the hierarchical clustering analysis of the band patterns of RAPD and the whole-cell protein profiles, four and five clusters were formed, respectively. It is showing the molecular diversity of P. multocida isolated from several regions in Indonesia. Molecular diversity was also observed based on sequence of the ompH gene which grouped P. multocida isolates used in this study into five clusters.
Keyword: Pasteurella multocida, protein profile, SDS-PAGE, RAPD, ompH, dendrogram

Judul: The Construction of Greedy SVP LLL Algorithm
Abstrak: A lattice is a set of all integer linear combination of a set of linearly independent vectors in ℝ𝑛���. The independent vectors are called bases of lattice. Any lattice can be generated from many bases, and these bases have the same cardinality. In the lattice, the most fundamental and renowned problem is the Shortest Vector Problem (SVP). SVP is a tracking problem of the shortest nonzero vector in a lattice with equivalent bases. In two dimensions, SVP problem has resolved exactly by Gauss’ algorithm. When the lattice dimension is higher than two, A.K. Lenstra, H.W. Lenstra and L. Lovasz gave a LLL algorithm to compute approximation of nonzero shortest vector in the lattice. Reduced bases solution obtained from LLL algorithm still be an approximation and has polynomial running time of arbitrary dimension which large enough. In 1994, Schnoor and Euchner modified this LLL algorithm as a new variant which later was named deep insertion LLL algorithm. This algorithm is a modified version of the LLL algorithm to the terms of the exchange step to improve the accuracy of output of LLL reduced bases and applying it to the subset sum problem. The purpose of this research are: (1) Reconstruct the LLL algorithm and deep insertion LLL algorithm using a geometric approach. (2) Construct a greedy SVP LLL algorithm. (3) Implement the three algorithms in a symbolic programming language, and evaluate them experimentally. A bases ℬ=[𝐛���1,𝐛���2,…,𝐛���𝑛���] in ℝ𝑚��� is called reduced LLL with parameter 𝛿��� if satisfies: (a) |𝜇���𝑗���𝑖���|≤12, for every integer 𝑖���,𝑗��� with 1≤𝑖���<𝑗���<𝑛���. (b)𝛿���‖𝜋���𝑗���(𝐛���𝑗���)‖2≤‖𝜋���𝑗���(𝐛���𝑗���+1)‖2, for 𝑗���=1,2,…,𝑛���−1,where 𝛿��� is a reduced parameter of real numbers with 14<𝛿���<1. The first requirement is the reduced basis 𝛿��� must “nearly orthogonal” and in its computation case, this requirement can be reached out by using the Gram-Schmidt’s orthogonalization. While the second requirement is called exchange step, or used to called as Lovasz condition. By using both of these requirements, then they establish the LLL algorithm. Then, Schnoor and Euchner modify the LLL algorithm based on the requirements of the exchange step called the deep insertion LLL algorithm, where the exchange step is based on the comparison of the projected vector in orthogonal complement [𝐛���1,𝐛���2,…,𝐛���𝑘���−1]⊥ after j-th reduction. To construct greedy SVP LLL algorithm, the requirements of the exchange step is based on purely by comparing norm of lattice 𝐛���𝑗��� with norm lattice 𝐛���𝑖��� for 𝑖���=1,2,3…,𝑗���−1. The process of insertion reduced vector after the exchange step also has done greedily. Then, we calculate the number of arithmetic operation in greedy SVP LLL algorithm for further analysis. The result of our exprimentation for three algorithms on the certain matrix size shows that the running time of the three algorithms increases propotional to the size of the matrix. The result also shows that by using 𝛿���=34 for the LLL algorithm and the deep insertion LLL algorithm, and the greedy SVP LLL algorithm which is a new variant made by using no parameter of 𝛿���, outperform of the other of two previous algorithm in terms of speed with the same output.
Keyword: LLL algorithm, LLL deep insertion algorithm, greedy SVP LLL algorithm