Perbandingan Pemberian Brodifakum Ld50 Dan Ld100 Terhadap Perubahan Gambaran Histopatologi Usus Halus Tikus Wistar

Background : Brodifacoum is an anticoagulant substance which usually used as pest control, but this substance has a poisoning effect the body. Brodifacoum is absorbed through gastrointestinal tract which can cause the disorder of blod clotting by slowing down the process of epoxide reductase of vitamin-K.Aim : To know the comparison of Histopathology Rattus norvegicus Intestine against brodifacoum administration LD50 and LD100.Methods :This study was an experimental study with post test only group design. The sample of this study are 27 Rattus norvegicus which given per oral administration of brodifacoum. Barthel Manja scores were used to assess changes in intestine Histopatology. Normal and desquamation are a minor damage, while erosion and ulcers are major damage. Non-parametric test of Mann-Whitney to the results are revealed significant if p <0.05.Results :On LD50, 2 rats died on days 3, 5 on day 5, and 2 rats terminated on day 7. In LD100 2 rats died on day 3, 2 on day 5, and 5 rats terminated on day 7. On LD50 groups there are 66,67% minor damage and 33,33% major damage, while in LD100 groups there are 55,56% minor damage and 44,44% major damage. Test non parametric Mann-Whitney in the control group with LD50 was found p = 0.269, in control group with LD100 was found p = 0106, then group with the LD50 and LD100 found p = 0.159.Conclusion :There are not significant differentiation of histopatology picture between LD50 and LD100 dose ( p = 0.159

Comparing multivariate regression and artificial neural network to predict barley production from soil characteristics in northern Iran

In this study artificial neural network (ANN) models were designed to predict the biomass and grain yield of barley from soil properties; and the performance of ANN models was compared with earlier tested statistical models based on multivariate regression. Barley yield data and surface soil samples (0–30 cm depth) were collected from 1 m2 plots at 112 selected points in the arid region of northern Iran. ANN yield models gave higher coefficient of determination and lower root mean square error compared to the multivariate regression, indicating that ANN is a more powerful tool than multivariate regression. Sensitivity analysis showed that soil electrical conductivity, sodium absorption ratio, pH, total nitrogen, available phosphorus, and organic matter consistently influenced barley biomass and grain yield. A comparison of the two methods to identify the most important factors indicated that while in the ANN analysis, soil organic matter (SOM) was included among the most important factors; SOM was excluded from the most important factors in the multivariate analysis. This significant discrepancy between the two methods was apparently a consequence of the non-linear relationships of SOM with other soil properties. Overall, our results indicated that the ANN models could explain 93 and 89% of the total variability in barley biomass and grain yield, respectively. The performance of the ANN models as compared to multivariate regression has better chance for predicting yield, especially when complex non-linear relationships exist among the factors. We suggest that for further potential improvement in predicting the barley yield, factors other than the soil properties considered such as soil micronutrient status and soil and crop management practices followed during the growing season, need to be included in the models

Relationships of barley biomass and grain yields to soil properties within a field in the arid region: Use of factor analysis

Understanding the variability of soil properties and their effects on crop yield is a critical component of site-specific management systems. The objective of this study was to employ factor and multiple regression analyses to determine major soil physical and chemical properties that influence barely biomass and grain yield within a field in the arid region of northern Iran. For this purpose, soil samples and crop-yield data were collected from 108 sites, at regular intervals (20 30 m) in a 5.6 ha field. Soil samples were analysed for total nitrogen (TN), available phosphorus (Pava), available potassium (Kava), cation-exchange capacity(CEC), electrical conductivity (EC), pH, mean weight diameter of aggregates (MWD), water-stable aggregates (WSA), field capacity volumetric (FC), available water-holding capacity (AWHC), bulk density (BD), and calcium carbonate equivalent (CCE). Results of the factor analysis, followed by regression of biomass and grain yield of barley with soil properties, showed that the regression equations developed accounted for 78 and 73% of the total variance in biomass and grain yield, respectively. Study of covariance analysis among soil variables using factor analysis indicated that some of the variation measured could be grouped to indicate a number of underlying common factors influencing barley biomass and grain yields. These common factors were salinity and sodicity, soil fertility, and water availability. The most effective soil variables to barley production in the study area identified as EC, SAR, pH, TN, Pava, AWHC, and FC. In this study, factor analysis was effective to identify the groups of correlated soil variables that were significantly correlated with the within field variability in the yield of the barley crop. Our results also suggest that the approach can be applied to other crops under similar soil and agroclimatic conditions

Soil Surface Salinity Prediction Using ASTER Data: Comparing Statistical and Geostatistical Models

This study was conducted to evaluate the performance of univariate spatial (ordinary kriging- OK), hybrid/multivariate geostatistical methods (regression-kriging- RK, Co-kriging- CK) with multivariate linear regression (MLR) in incorporation with ASTER data in order to predict the spatial variability of surface soil salinity in an arid area in northern Iran. The primary attributes were obtained from grid soil sampling with nested-systematic pattern of 169 samples and the secondary information extracted from spectral data of ASTER satellite images. The principal component analysis, NDVI and some suitable ratioing bands were applied to generate new arithmetic bands. According to validation based RMSE and ME calculated by a validation data set, the predictions for soil salinity were found to be the best and varied in the following order: RK ASTERmultivariate > REG ASTERmultivariate > Co-kriging ASTER> kriging. Overall, this comparative study demonstrated that RK approach was a better predicator than other selected methods to predict spatial variability of soil salinity. The overall results confirmed that using ancillary variables such as remotely sensed data, the accuracy of spatial prediction can further improved

Relationships between soil depth and terrain attributes in a semi arid hilly region in western Iran

Soil depth generally varies in mountainous regions in rather complex ways. Conventional soil survey methods for evaluating the soil depth in mountainous and hilly regions require a lot of time, effort and consequently relatively large budget to perform. This study was conducted to explore the relationships between soil depth and topographic attributes in a hilly region in western Iran. For this, one hundred sampling points were selected using randomly stratified methodology, and considering all geomorphic surfaces including summit, shoulder, backslope, footslope and toeslope; and soil depth was actually measured. Eleven primary and secondary topographic attributes were derived from the digital elevation model (DEM) at the study area. The result of multiple linear regression indicated that slope, wetness index, catchment area and sediment transport index, which were included in the model, could explain about 76 % of total variability in soil depth at the selected site. This proposed approach may be applicable to other hilly regions in the semi-arid areas at a larger scale

The ATF6-Met [67] Val substitution is associated with increased plasma cholesterol levels

Objective— Activating transcription factor 6 (ATF6) is a sensor of the endoplasmic reticulum stress response and regulates expression of several key lipogenic genes. We used a 2-stage design to investigate whether ATF6 polymorphisms are associated with lipids in subjects at increased risk for cardiovascular disease (CVD). Methods and Results— In stage 1, 13 tag-SNPs were tested for association in Dutch samples ascertained for familial combined hyperlipidemia (FCHL) or increased risk for CVD (CVR). In stage 2, we further investigated the SNP with the strongest association from stage 1, a Methionine/Valine substitution at amino-acid 67, in Finnish FCHL families and in subjects with CVR from METSIM, a Finnish population-based cohort. The combined analysis of both stages reached region-wide significance (P=9x10–4), but this association was not seen in the entire METSIM cohort. Our functional analysis demonstrated that Valine at position 67 augments ATF6 protein and its targets Grp78 and Grp94 as well as increases luciferase expression through Grp78 promoter. Conclusions— A common nonsynonymous variant in ATF6 increases ATF6 protein levels and is associated with cholesterol levels in subjects at increased risk for CVD, but this association was not seen in a population-based cohort. Further replication is needed to confirm the role of this variant in lipids. We report the association of the ATF6-methionine [67]valine amino-acid substitution with plasma cholesterol levels. Association analyses in 2674 subjects and functional data suggest that the ATF6 gene may influence cholesterol levels in subjects at increased risk to develop cardiovascular disease

Contribution à la dépollution des eaux usées de textile par électrocoagulation et par adsorption sur des composés à base de fer et d’aluminium

Les ressources hydriques au monde sont rares et la demande en eau connaît une croissance continue en liaison avec l’évolution démographique et les activités consommatrices en eau, notamment les industries de textiles se voient dans l’obligation de recycler les eaux résiduaires et en particulier celles colorées. Dans ce travail, nous nous sommes intéressés à l’étude de l’élimination des matières organiques et colorantes de deux rejets provenant des industries de textile, un de teinture du tissu de polyester à pH acide et l’autre de teinture du tissu de coton à pH basique. Ces rejets ont été traités de deux manières. La première est par électrocoagulation en utilisant des plaques de fer et/ou d’aluminium. La deuxième est par adsorption sur des composés synthétiques à base de fer et d’aluminium préparés par électrocoagulation. Dans le cas du traitement par le procédé d’électrocoagulation, nous avons constaté que le rendement d’élimination en demande chimique en oxygène (DCO) du rejet de polyester atteint un rendement de DCO de 60% pour un temps de 7 min de réaction. Pour le rejet de coton, le rendement d’élimination, par les plaques de fer/aluminium et l’élimination des matières colorantes, atteint une valeur de 45% en terme de DCO, et ceci en utilisant des plaques d’aluminium seul et de fer/aluminium pour un temps de 12 et 15 min respectivement. Dans le cas du traitement par ajout des coagulants synthétiques préparés au laboratoire, nous pouvons observer que le meilleur rendement d’élimination en DCO du rejet de polyester est obtenu pour une valeur de 48%, pour la faible granulométrie avec une concentration de 5 g/l du composé à base de fer /aluminium. Le rendement d’élimination en DCO du rejet de coton augmente jusqu'à une valeur de 60% avec une concentration de 5 g/l de coagulants appliqués à base d’aluminium seul. Les résultats de la dépollution de ces rejets, ont montré que le rendement d'élimination des matières organiques et colorantes par le procédé d'électrocoagulation est important, et la durée de traitement est courte, mais l'inconvénient de ce procédé c'est la saleté des plaques après chaque utilisation et la fabrication d'une grande quantité des boues par rapport à l’adsorption sur des composés à base de fer /aluminium où on utilise des poudres peu solubles et stables avec un bon rendement d’élimination et faibles quantités de fer et d'aluminium dans le surnageant traité.Keywords: Colorant textile, électrocoagulation, adsorption, dépollution, fer, aluminiu

Pasture degradation effects on soil quality indicators at different hillslope positions in a semiarid region of western Iran

A study was made to determine the influence of pasture degradation on soil quality indicators that included physical, chemical, biological and micromorphological attributes, along the hillslope positions in Chaharmahal and Bakhtiari province, western Iran. Soil samples from different slope positions were collected from 0 to 30 cm depth for physical and chemical properties and from 0 to 15 cm depth for biological properties at two adjacent sites in the two ecosystems: natural pasture and cultivated land. Soil quality indicators including bulk density, mean weight diameter, soil organic carbon (SOC), particulate organic material (POM) in aggregate fractions, total nitrogen, available potassium, available phosphorus, cation exchange capacity, soil microbial respiration (SMR) and microbial biomass C and N were determined. The results showed that SOC decreased cultivation from 1.09 to 0.77 % following pasture degradation. The POM decreased by about 19.35 % in cultivated soils when compared to natural pasture; also, SMR and microbial biomass C and N decreased significantly following pasture degradation. Furthermore, aggregate stability and pore spaces decreased, and bulk density increased in the cultivated soils. Overall, our results showed that long-term cultivation following pasture degradation led to a decline in soil quality in all selected slope positions at the site studied in the semiarid region

Assessing Impacts of Land Use Change on Soil Quality Indicators in a Loessial Soil in Golestan Province, Iran

A study was conducted to determine suitable soil properties as soil quality indicators, using factor analysis in order to evaluate the effects of land use change on loessial hillslope soils of the Shastkola District in Golestan Province, northern Iran. To this end, forty surface soil (0-30 cm) samples were collected from four adjacent sites with the following land uses systems: (1) natural forest, (2) cultivated land, (3) land reforested with olive, and (4) land reforested with Cupressus. Fourteen soil chemical, physical, and biological properties were measured. Factor analysis (FA) revealed that mean weight diameter (MWD), water stable aggregates (WSA), soil organic matter (SOM), and total nitrogen (TN) were suitable for assessing the soil quality in the given ecosystem for monitoring the land use change effects. The results of analysis of variance (ANOVA) and mean comparison showed that there were significant (P< 0.01) differences among the four treatments with regard to SOM, MWD, and sand content. Clearing of the hardwood forest and tillage practices during 40 years led to a decrease in SOM by 71.5%. Cultivation of the deforested land decreased MWD by 52% and increased sand by 252%. The reforestation of degraded land with olive and Cupressus increased SOM by about 49% and 72%, respectively, compared to the cultivated control soil. Reforestation with olive increased MWD by 81% and reforestation with Cupressus increased MWD by 83.6%. The study showed that forest clearing followed by cultivation of the loessial hilly slopes resulted in the decline of the soil quality attributes, while reforestation improved them in the study area

Relation Between Age and Unplanned Readmissions After Percutaneous Coronary Intervention (Findings from the Nationwide Readmission Database))

Acknowledgements: We are grateful to the Healthcare Cost and Utilization Project (HCUP) and the HCUP Data Partners for providing the data used in the analysis. List of Supports/Grants Information: The study was supported by a grant from the Research and Development Department at the Royal Stoke Hospital. This work is conducted as a part of PhD for CSK which is supported by Biosensors International.Peer reviewedPostprin