• Membrane and Water Treatment
• /
• v.10 no.2
• /
• pp.121-125
• /
• 2019

Chronic exposure to atrazine (ATR) raises concerns about adverse effects on reproductive functions. We tested our previously validated filtering device, the OBP-based filter, onto a biological model constituted of cultured swine granulosa cells treated for 48 h with media conditioned with 0.1 or $10{\mu}M$ ATR evaluating cell viability and steroidogenesis. The tested atrazine concentrations did not change granulosa cell viability and no filtering effects was observed following treatments with media prepared with differently filtered water. As for steroidogenesis, treatment of water with OBP-based filter containing $10{\mu}M$ atrazine completely suppressed the stimulatory effect of $10{\mu}M$ atrazine on progesterone production as well as the inhibitory effect of $0.1{\mu}M$ ATR on estradiol-$17{\beta}$ production by granulosa cells. Our data demonstrate that the impairment of steroidogenesis induced by ATR is effectively removed after water filtration in the experimental device thus suggesting potential use in biotechnological applications on living cells and/or organisms.

• Journal of Periodontal and Implant Science
• /
• v.46 no.4
• /
• pp.220-233
• /
• 2016

Purpose: The aim of this study was to present new a model that allows the study of the bone healing process, with an emphasis on the biological behavior of different graft-to-host interfaces. A standardized "over-inlay" surgical technique combined with a differential histomorphometric analysis is presented in order to optimize the use of critical-size calvarial defects in pre-clinical testing. Methods: Critical-size defects were created into the parietal bone of 8 male Wistar rats. Deproteinized bovine bone (DBBM) blocks were inserted into the defects, so that part of the block was included within the calvarial thickness and part exceeded the calvarial height (an "over-inlay" graft). All animals were sacrificed at 1 or 3 months. Histomorphometric and immunohistochemical evaluation was carried out within distinct regions of interest (ROIs): the areas adjacent to the native bone (BA), the periosteal area (PA) and the central area (CA). Results: The animals healed without complications. Differential morphometry allowed the examination of the tissue composition within distinct regions: the BA presented consistent amounts of new bone formation (NB), which increased over time ($24.53%{\pm}1.26%$ at 1 month; $37.73%{\pm}0.39%$ at 3 months), thus suggesting that this area makes a substantial contribution toward NB. The PA was mainly composed of fibrous tissue ($71.16%{\pm}8.06%$ and $78.30%{\pm}2.67%$, respectively), while the CA showed high amounts of DBBM at both time points ($78.30%{\pm}2.67%$ and $74.68%{\pm}1.07%$, respectively), demonstrating a slow remodeling process. Blood vessels revealed a progressive migration from the interface with native bone toward the central area of the graft. Osterix-positive cells observed at 1 month within the PA suggested that the periosteum was a source of osteoprogenitor elements. Alkaline phosphatase data on matrix deposition confirmed this observation. Conclusions: The present model allowed for a standardized investigation of distinct graft-to-host interfaces both at vertically augmented and inlay-augmented sites, thus possibly limiting the number of animals required for pre-clinical investigations.

• KSCE Journal of Civil and Environmental Engineering Research
• /
• v.28 no.2B
• /
• pp.199-213
• /
• 2008

The goal of this research is to develop and apply the integrational operation method (IOM) for the modeling of the monthly pan evaporation (PE) and the alfalfa reference evapotranspiration ($ET_r$). Since the observed data of the alfalfa $ET_r$ using lysimeter have not been measured for a long time in Republic of Korea, Penman-Monteith (PM) method is used to estimate the observed alfalfa $ET_r$. The IOM consists of the application of the stochastic and neural networks models, respectively. The stochastic model is applied to generate the training dataset for the monthly PE and the alfalfa $ET_r$, and the neural networks models are applied to calculate the observed test dataset reasonably. Among the considered six training patterns, 1,000/PARMA(1,1)/GRNNM-GA training pattern can evaluate the suggested climatic variables very well and also construct the reliable data for the monthly PE and the alfalfa $ET_r$. Uncertainty analysis is used to eliminate the climatic variables of input nodes from 1,000/PARMA(1,1)/GRNNM-GA training pattern. The sensitive and insensitive climatic variables are chosen from the uncertainty analysis of the input nodes. Finally, it can be to model the monthly PE and the alfalfa $ET_r$ simultaneously with the least cost and endeavor using the IOM.

• Journal of Korea Water Resources Association
• /
• v.36 no.2
• /
• pp.195-209
• /
• 2003

Spatial-Stochastic Neural Networks Model(SSNNM) is used to estimate long-term streamflow in the parallel reservoir groups. SSNNM employs two kinds of backpropagation algorithms, based on LMBP and BFGS-QNBP separately. SSNNM has three layers, input, hidden, and output layer, in the structure and network configuration consists of 8-8-2 nodes one by one. Nodes in input layer are composed of streamflow, precipitation, pan evaporation, and temperature with the monthly average values collected from Andong and Imha reservoir. But some temporal differences apparently exist in their time series. For the SSNNM training procedure, the training sets in input layer are generated by the PARMA(1,1) stochastic model and they covers insufficient time series. Generated data series are used to train SSNNM and the model parameters, optimal connection weights and biases, are estimated during training procedure. They are applied to evaluate model validation using observed data sets. In this study, the new approaches give outstanding results by the comparison of statistical analysis and hydrographs in the model validation. SSNNM will help to manage and control water distribution and give basic data to develop long-term coupled operation system in parallel reservoir groups of the Upper Nakdong River.

• Animal Bioscience
• /
• v.36 no.1
• /
• pp.132-143
• /
• 2023

Objective: The aim was to study the influence of cooling milk at 9℃ at the farm versus keeping it at 20℃ on Parmigiano Reggiano cheese lipolysis. Methods: A total of six cheesemaking trials (3 in winter and 3 in summer) were performed. In each trial, milk was divided continuously into two identical aliquots, one of which was kept at 9℃ (MC9) and the other at 20℃ (MC20). For each trial and milk temperature, vat milk (V-milk) and the resulting 21 month ripened cheese were analysed. Results: Fat and dry matter and fat/casein ratio were lower in MC9 V-milk (p≤0.05) than in MC20. Total bacteria, mesophilic lactic acid and psychrotrophic and lipolytic bacteria showed significant differences (p≤0.05) between the two V-milks. Regarding cheese, fat content resulted lower and crude protein higher (p≤0.05) both in outer (OZ) and in inner zone (IZ) of the MC9 cheese wheels. Concerning total fatty acids, the MC9 OZ had a lower concentration of butyric, capric (p≤0.05) and medium chain fatty acids (p≤0.05), while the MC9 IZ had lower content of butyric (p≤0.05), caproic (p≤0.01) and short chain fatty acids (p≤0.05). The levels of short chain and medium chain free fatty acids (p≤0.05) were lower and that of long chain fatty acids (p≤0.05) was higher in MC9 OZ cheese. The principal component analysis of total and free fatty acids resulted in a clear separation among samples by seasons, whereas slight differences were observed between the two different milk temperatures. Conclusion: Storing milk at 9℃ at the herd affects the chemical composition of Parmigiano Reggiano, with repercussion on lipolysis. However, the changes are not very relevant, and since the cheese can present a high variability among the different cheese factories, such changes should be considered within the "normal variations" of Parmigiano Reggiano chemical characteristics.

• Archives of Pharmacal Research
• /
• v.28 no.12
• /
• pp.1317-1323
• /
• 2005

In an attempt to examine the ability of benzisothiazole-based drugs to interact with $\beta$-adrenoceptors, a series of 1,2-benzisothiazole derivatives, which were substituted with various propanolamine or oxypropanolamine side chains in the 2 or 3 position, were synthesised and tested. The pharmacological activity of these compounds at the ,$\beta$-adrenoceptors was examined using isolated rat atria and small intestinal segments, which preferentially express the $\beta_{1}$- and $\beta_{3}$-adrenoceptor-mediated responses, respectively. None of these products showed any $\beta$-adrenoceptor agonistic activity. In contrast, the 2- and 3-substituted isopropyl, tert-butyl, benzyl, and piperonyl derivatives 2a-d and 3a-d elicited surmountable inhibition of the isoprena­line-induced chronotropic effects in the atria, suggesting competitive antagonism at the $\beta_{1}$­recognition site. The $pA_{2}$ values revealed tert-butyl 3b and the isopropyl substituted piperonyl derivatives 3a to be the most effective. Remarkably, many of the 2-substituted propanolamines were less active than the corresponding 3-substituted oxypropanolamines. With the exception of compound 3b, none of these drugs antagonised the muscle relaxant activity of isoprenaline in the intestine, suggesting no effect on the $\beta_{3}$-adrenoceptors. These results confirm the ability of the benzisothiazole ring to interact with the $\beta$-adrenoceptors, and demonstrate that 2-substitution with propanolamine or 3-substitution with oxypropanolamine groups yields compounds with preferential antagonistic activity at the cardiac $\beta_{1}$adrenoceptors. The degree of antagonism depends strongly on both the nature of the substituent and its position on the benzisothiazole ring.

• Proceedings of the Korea Water Resources Association Conference
• /
• 2009.05a
• /
• pp.1215-1218
• /
• 2009

The goal of this research is to apply the neural networks models for the disaggregation of the pan evaporation (PE) data, Republic of Korea. The neural networks models consist of generalized regression neural networks model (GRNNM) and multilayer perceptron neural networks model (MLP-NNM), respectively. The disaggregation means that the yearly PE data divides into the monthly PE data. And, for the performances of the neural networks models, they are composed of training and test performances, respectively. The training data consist of the mixed data The mixed data involves the historic data and the generated data using PARMA (1,1). And, the testing data consist of the only historic data, respectively. From this research, we evaluate the impact of GRNNM and MLP-NNM for the disaggregation of the nonlinear time series data. We should, furthermore, construct the credible data of the monthly PE data from the disaggregation of the yearly PE data, and can suggest the methodology for the irrigation and drainage networks system.

• Proceedings of the Korea Water Resources Association Conference
• /
• 2009.05a
• /
• pp.1211-1214
• /
• 2009

The goal of this research is to apply the neural networks models for the disaggregation of the pan evaporation (PE) data, Republic of Korea. The neural networks models consist of generalized regression neural networks model (GRNNM) and multilayer perceptron neural networks model (MLP-NNM), respectively. The disaggregation means that the yearly PE data divides into the monthly PE data. And, for the performances of the neural networks models, they are composed of training and test performances, respectively. The training data consist of the generated data using PARMA (1,1). And, the testing data consist of the historic data, respectively. From this research, we evaluate the impact of GRNNM and MLP-NNM for the disaggregation of the nonlinear time series data. We should, furthermore, construct the credible data of the monthly PE data from the disaggregation of the yearly PE data, and can suggest the methodology for the irrigation and drainage networks system.

• Animal Bioscience
• /
• v.37 no.5
• /
• pp.862-874
• /
• 2024

Objective: This study evaluated the effect of Andrographis paniculata (A. paniculata) supplementation in sow diets before and after farrowing on the sow and piglets' performances during early postpartum period and on sows' backfat and longissimus muscle losses during lactation. Methods: Seventy Landrace×Yorkshire sows and their offspring (1,186 piglets) were distributed into three groups: control (n = 31), treatment-250 (n = 18), and treatment-1000 (n = 21). From 110.2±0.7 days of gestation until farrowing (5.8 days) and throughout the lactation period (25.2 days), sows in the control group were given the conventional lactation diet, while sows in the treatment-250 and treatment-1000 groups received supplements of 250 ppm and 1,000 ppm of A. paniculata, respectively. Results: In sows with parity 3-5, piglets from the treatment-1000 group had higher colostrum intake than the control and treatment-250 groups (p<0.05), but not in sows with parity 6-9. Colostrum immunoglobulin G (IgG) increased in treated sows versus controls for parity 6-9 (p<0.05), but was consistent for parity 3-5. Piglet performance until day 3 postnatal was similar across groups (p>0.05). Treatment-250 sows had higher feed intake post-farrowing than treatment-1000 sows (p<0.05). Longissimus loss was less in both treatment groups than control (p<0.05), but backfat loss was similar across groups (p>0.05). Post-partum complications were consistent across groups (p>0.05). Farrowing duration and piglet birth intervals in sows with parity 6-9 were prolonged in the treatment-1000 group. Conclusion: Supplementing with 1,000 ppm A. paniculata for 5.8 days pre-farrowing and 25.2 days post-farrowing enhanced sow colostrum IgG and piglet colostrum intake, while also reducing longissimus loss in sows. However, for sows of parity 6-9, this supplementation led to prolonged farrowing, increased intervals between piglet births, increased stillbirth, and reduced piglet birth weight. These effects should be considered when using A. paniculata supplementation.

• Animal Bioscience
• /
• v.34 no.5
• /
• pp.833-843
• /
• 2021

Objective: Current study was conducted to determine the effect of postpartum prostaglandin F2α (PGF2α) administration on colostrum and milk yield, colostrum immunoglobulin G (IgG) and piglet growth performance. Methods: In total, 36 sows were included in the experiment. The sows were classified into two groups: i) control (n = 11) and ii) PGF2α (n = 25). Sows in the PGF2α group received 10 mg of PGF2α within an hour after farrowing. The body weight of piglets was measured at 0 and 24 h after birth to estimate colostrum consumption. Colostrum was collected at 1 and 24 h after farrowing to determine IgG concentrations. For milk yield study, the remaining sows in the PGF2α group (n = 23) were divided into two subgroups: i) single PGF2α (n = 12) and ii) multiple PGF2α (n = 11). In the multiple PGF2α, the sows received repeated doses of PGF2α at seven and 14 days postpartum. The piglets' body weight was measured at 0, 1, 5, and 20 days of age. The milk yield of the sows was calculated. Results: Colostrum yield of sows averaged 5.62±2.25 kg. Sows treated with PGF2α postpartum had a higher colostrum yield than control (7.01 and 5.12 kg, p<0.05). The concentration of IgG in colostrum at 24 h in the PGF2α group was higher than the control (31.6 and 17.4 g/L, p<0.05). For primiparous sows, milk yield was highest in the sows treated with multiple doses of PGF2α during lactation and lowest in control sows (10.25 and 7.61 kg, p<0.05). Colostrum intake was higher in the treatment than the control groups (+56.7 g, p<0.05). Primiparous sows treated with multiple doses of PGF2α had a higher litter weight than controls (p<0.01). Conclusion: Postpartum treatment with PGF2α improved colostrum yield and IgG in multiparous sows and increased colostrum intake of piglets. Multiple administration of PGF2α improved the milk yield and increased litter weight of piglets in primiparous sows.