Systemic IL-1β and TNF-α Productions of E. Coli Lipopolysaccharide-Induced Periodontitis Model on Rats

Periodontal disease, a common inflammatory oral disease involved periodontal tissues, has been linked with the evidence of some systemic disorders. Recently, periodontal disease has been suspected as a trigger of systemic disorders. Penetration of bacterial products, such as lipopolysaccharide (LPS) may reach into deeper periodontal tissues. Therefore there may affect systemic blood and cytokines production. Interleukin-1β (IL-1β) and Tumour Nuclear Factor-α (TNF-α) are known as pro-inflammatory cytokines. The production of systemic IL-1β and TNF-α of E. coli lipopolysaccharide-induced periodontitis model on rats was investigated in this research. Fifteen male Wistar rats, aged 6-8 weeks used for this study were divided into 3 groups. For group 1 and 2, silk ligature 3/0 were inserted in interdental area between upper right molar 1 and 2. First and second group received solution containing 10μg/ml and 1mg/ml E. coli lipopolysaccharide, respectively, mixedwith 2% carboxymethylcellulose (CMC) diluted in 100μl of phosphate buffer saline (PBS). The solution was topically applied on gingival tissues around the gingival sulcus, a single topical application of solution onceper 2 days for 14 days. Untreated subjects were used as negative control. On day 15, the blood was collected from vena orbitalis, and rats were sacrificed. The blood serum of each group was divided into 2 groups andcultured for 4 hours with or without 20μl of 100ng/ml of E. coli LPS. ELISA techniques were used to measure the cytokine productions of the supernatant. The data was analysed using Repeated Measure ANOVA. This study showed that there was a significant increase of IL-1β production on low dose of LPS compared to control and high dose of LPS groups (p<0.05). Whereas TNF-α not significantly showed increasing trend. The increasing trend of pro-inflammatory cytokine productions, such as IL-1β and TNF-α, on LPS-induced periodontitis model in this experiment supports the previous studies about the contribution of periodontal disease in the pathogenesis of systemic diseases

Influence of Different Energy-Proteins on Performance and Blood Hematological on Three Types of Local Chicken

Indonesia is rich in germplasm, including local chickens. Three types of superior local chickens are Sentul-Warso Chicken, Chicken Kampung-Unggul, and Chicken Local-Jimy. Chickens are relatively diverse growth and nutrient needs are also variations, especially energy and protein content. The research has been conducted at Test Farm cage, Faculty of Animal Husbandry, University of Padjadjaran, Sumedang, and West Java-Indonesia. The objective of the study was to determine the energy-protein requirements of the ration, which resulted in the highest production performance and optimal hematologic blood values in three types of local chickens (Sentul-Warso Chicken, Chicken Kampung-Unggul, and Chicken Local-Jimy). Research using experimental method in laboratory. The experimental design was a Completely Randomized Design, consisting of five treatment rations with different energy and protein levels and each repeated four times. The treatment consisted of: R1 = EM 2750 kcal / kg and PK 15%; R2 = EM 2750 kcal / kg and PK 17%; R3 = EM 2750 kcal / kg and PK 19%; R4 = EM 2950 kcal / kg and PK 15%; and R5 = EM 2950 kcal / kg and PK 17%. The data were analyzed by means of variation and the differences between treatments were tested with Duncan Multiple Range Test. The result showed that ration with metabolic energy content 2,750 kcal / kg and 17% crude protein resulted in optimal production and hematological blood value in local chicken. The performance of Chicken-Jimy's production is higher than Sentul-Warso chicken and the lowest Kampung-Unggul chicken. The hematological value of chicken blood is in the normal range

TRY plant trait database - enhanced coverage and open access

Plant traits-the morphological, anatomical, physiological, biochemical and phenological characteristics of plants-determine how plants respond to environmental factors, affect other trophic levels, and influence ecosystem properties and their benefits and detriments to people. Plant trait data thus represent the basis for a vast area of research spanning from evolutionary biology, community and functional ecology, to biodiversity conservation, ecosystem and landscape management, restoration, biogeography and earth system modelling. Since its foundation in 2007, the TRY database of plant traits has grown continuously. It now provides unprecedented data coverage under an open access data policy and is the main plant trait database used by the research community worldwide. Increasingly, the TRY database also supports new frontiers of trait-based plant research, including the identification of data gaps and the subsequent mobilization or measurement of new data. To support this development, in this article we evaluate the extent of the trait data compiled in TRY and analyse emerging patterns of data coverage and representativeness. Best species coverage is achieved for categorical traits-almost complete coverage for 'plant growth form'. However, most traits relevant for ecology and vegetation modelling are characterized by continuous intraspecific variation and trait-environmental relationships. These traits have to be measured on individual plants in their respective environment. Despite unprecedented data coverage, we observe a humbling lack of completeness and representativeness of these continuous traits in many aspects. We, therefore, conclude that reducing data gaps and biases in the TRY database remains a key challenge and requires a coordinated approach to data mobilization and trait measurements. This can only be achieved in collaboration with other initiatives

TRY plant trait database - enhanced coverage and open access

This article has 730 authors, of which I have only listed the lead author and myself as a representative of University of HelsinkiPlant traits-the morphological, anatomical, physiological, biochemical and phenological characteristics of plants-determine how plants respond to environmental factors, affect other trophic levels, and influence ecosystem properties and their benefits and detriments to people. Plant trait data thus represent the basis for a vast area of research spanning from evolutionary biology, community and functional ecology, to biodiversity conservation, ecosystem and landscape management, restoration, biogeography and earth system modelling. Since its foundation in 2007, the TRY database of plant traits has grown continuously. It now provides unprecedented data coverage under an open access data policy and is the main plant trait database used by the research community worldwide. Increasingly, the TRY database also supports new frontiers of trait-based plant research, including the identification of data gaps and the subsequent mobilization or measurement of new data. To support this development, in this article we evaluate the extent of the trait data compiled in TRY and analyse emerging patterns of data coverage and representativeness. Best species coverage is achieved for categorical traits-almost complete coverage for 'plant growth form'. However, most traits relevant for ecology and vegetation modelling are characterized by continuous intraspecific variation and trait-environmental relationships. These traits have to be measured on individual plants in their respective environment. Despite unprecedented data coverage, we observe a humbling lack of completeness and representativeness of these continuous traits in many aspects. We, therefore, conclude that reducing data gaps and biases in the TRY database remains a key challenge and requires a coordinated approach to data mobilization and trait measurements. This can only be achieved in collaboration with other initiatives.Peer reviewe

TRY plant trait database – enhanced coverage and open access

Plant traits—the morphological, anatomical, physiological, biochemical and phenological characteristics of plants—determine how plants respond to environmental factors, affect other trophic levels, and influence ecosystem properties and their benefits and detriments to people. Plant trait data thus represent the basis for a vast area of research spanning from evolutionary biology, community and functional ecology, to biodiversity conservation, ecosystem and landscape management, restoration, biogeography and earth system modelling. Since its foundation in 2007, the TRY database of plant traits has grown continuously. It now provides unprecedented data coverage under an open access data policy and is the main plant trait database used by the research community worldwide. Increasingly, the TRY database also supports new frontiers of trait‐based plant research, including the identification of data gaps and the subsequent mobilization or measurement of new data. To support this development, in this article we evaluate the extent of the trait data compiled in TRY and analyse emerging patterns of data coverage and representativeness. Best species coverage is achieved for categorical traits—almost complete coverage for ‘plant growth form’. However, most traits relevant for ecology and vegetation modelling are characterized by continuous intraspecific variation and trait–environmental relationships. These traits have to be measured on individual plants in their respective environment. Despite unprecedented data coverage, we observe a humbling lack of completeness and representativeness of these continuous traits in many aspects. We, therefore, conclude that reducing data gaps and biases in the TRY database remains a key challenge and requires a coordinated approach to data mobilization and trait measurements. This can only be achieved in collaboration with other initiatives

TRY plant trait database - enhanced coverage and open access

Plant traits—the morphological, anatomical, physiological, biochemical and phenological characteristics of plants—determine how plants respond to environmental factors, affect other trophic levels, and influence ecosystem properties and their benefits and detriments to people. Plant trait data thus represent the basis for a vast area of research spanning from evolutionary biology, community and functional ecology, to biodiversity conservation, ecosystem and landscape management, restoration, biogeography and earth system modelling. Since its foundation in 2007, the TRY database of plant traits has grown continuously. It now provides unprecedented data coverage under an open access data policy and is the main plant trait database used by the research community worldwide. Increasingly, the TRY database also supports new frontiers of trait‐based plant research, including the identification of data gaps and the subsequent mobilization or measurement of new data. To support this development, in this article we evaluate the extent of the trait data compiled in TRY and analyse emerging patterns of data coverage and representativeness. Best species coverage is achieved for categorical traits—almost complete coverage for ‘plant growth form’. However, most traits relevant for ecology and vegetation modelling are characterized by continuous intraspecific variation and trait–environmental relationships. These traits have to be measured on individual plants in their respective environment. Despite unprecedented data coverage, we observe a humbling lack of completeness and representativeness of these continuous traits in many aspects. We, therefore, conclude that reducing data gaps and biases in the TRY database remains a key challenge and requires a coordinated approach to data mobilization and trait measurements. This can only be achieved in collaboration with other initiatives

TRY plant trait database – enhanced coverage and open access

Plant traits - the morphological, anatomical, physiological, biochemical and phenological characteristics of plants - determine how plants respond to environmental factors, affect other trophic levels, and influence ecosystem properties and their benefits and detriments to people. Plant trait data thus represent the basis for a vast area of research spanning from evolutionary biology, community and functional ecology, to biodiversity conservation, ecosystem and landscape management, restoration, biogeography and earth system modelling. Since its foundation in 2007, the TRY database of plant traits has grown continuously. It now provides unprecedented data coverage under an open access data policy and is the main plant trait database used by the research community worldwide. Increasingly, the TRY database also supports new frontiers of trait‐based plant research, including the identification of data gaps and the subsequent mobilization or measurement of new data. To support this development, in this article we evaluate the extent of the trait data compiled in TRY and analyse emerging patterns of data coverage and representativeness. Best species coverage is achieved for categorical traits - almost complete coverage for ‘plant growth form’. However, most traits relevant for ecology and vegetation modelling are characterized by continuous intraspecific variation and trait–environmental relationships. These traits have to be measured on individual plants in their respective environment. Despite unprecedented data coverage, we observe a humbling lack of completeness and representativeness of these continuous traits in many aspects. We, therefore, conclude that reducing data gaps and biases in the TRY database remains a key challenge and requires a coordinated approach to data mobilization and trait measurements. This can only be achieved in collaboration with other initiatives

Pengembangan Aplikasi Kriptografi File Audio dengan Algoritma Data Encryption Standard (DES)

Keamanan data merupakan salah satu isu penting di era teknologi informasi dan komunikasi. Salah satu alternatif untuk menjaga keamanan data adalah dengan mengembangkan aplikasi yang menerapkan algoritma kriptografi. Penelitian ini bertujuan untuk merancang dan mengembangkan sebuah aplikasi kriptografi yang mengimplementasikan algoritma Data Encryption Standard (DES). Perancangan sistem aplikasi ini menggunakan UML (Unified Modeling Language) dengan enkripsi dan dekripsi file WAV sebagai rancangan utama. Proses enkripsi dan dekripsi ini menggunakan algoritma DES. Algoritma DES merupakan algoritma kriptografi simetri yaitu algoritma kriptografi yang menggunakan kunci yang sama untuk enkripsi dan dekripsi. Algortima DES bekerja pada blok data 64 bit dan menggunakan panjang kunci 64 bit. Proses-proses yang terdapat pada algoritma DES meliputi pembangkitan kunci internal, permutasi awal, enchipering, dan permutasi akhir. Implementasi Algoritma DES pada aplikasi kriptografi file audio menghasilkan sebuah perangkat lunak yang disebut dengan AudioEncryptor. Berdasarkan hasil pengujian perangkat lunak diperoleh bahwa AudioEncryptor mampu mengenkripsi file audio dengan baik. Suara yang dikeluarkan file audio terenkripsi tidak sama dengan suara sebenarnya, sehingga kerahasiaan informasi yang terkandung dalam file audio yang sudah dienkripsi sangat aman. Selain enkripsi dan dekripsi, AudioEncryptor juga dilengkapi dengan Fasilitas record dan play audio yaitu Fasilitas untuk merekam dan memutar file audio. Perangkat Lunak AudioEncryptor sendiri dikembangkan dengan menggunakan bahasa pemrograman Java yaitu pada lingkungan Java 2 Standard Edition (J2SE)