• Korean Journal of Environmental Biology
• /
• v.22 no.4
• /
• pp.524-531
• /
• 2004

Photosynthetic activities and primary production of phytoplankton were investigated in Lake Gocheonam from October 1999 to August 2000. As an estuary lake with a barrage in the Southwestern coast of the Korean peninsula, the lake has received more attention after it became known as the habitat of large population of rare and endangered bird- Baikal Teal. As the lake had high algal biomass ranging from $20\mu{g}\;chl-aL^{-1}\;to\;125\mu{g}\;chl-aL^{-1}$ in average values and rich eutrophication indicator species, the freshwaters were in a very productive or hypertrophic state. In the results obtained from the phytoplankton incubation in the laboratory, the maximum photosynthetic rate $(P_{max})$ varied according to seasons and sampling stations. Photo- synthetic activities were higher during the warm season than the cold seasons and the serial order of $P_{max}$ was August dominated with Microcystis, April with Chlamydomonas and Nitzschia, October with Chlamydomonas and January with Stephanodiscus. The water of the lake was persistently turbid throughout the year due to strong winds from the adjacent sea. Despite the water turbidity, the phytoplankton productions estimated from a mathematical model had very broad range from 18mg C $m^{-2}day^{-1}\;to\;10,300mg\;C\;m^{-2}day^{-1}$.

• Korean Journal of Environmental Biology
• /
• v.39 no.3
• /
• pp.298-310
• /
• 2021

Prediction of the behavior of heavy metals over time is important to evaluate the heavy metal toxicity in algae species. Various modeling studies have been well established, but there is a need for an improved model for predicting the chronic effects of metals on algae species to combine the metal kinetics and biological response of algal cells. In this study, a kinetic dynamics model was developed to predict the copper behavior(5 ㎍ L^-1, 10 ㎍ L^-1, and 15 ㎍ L^-1) for two freshwater algae (Pseudokirchneriella subcapitata and Chlorella vulgaris) in the chronic exposure experiments (8 d and 21 d). In the experimental observations, the rapid change in copper mass between the solutions, extracellular and intracellular sites occurred within initial exposure periods, and then it was slower although the algal density changed with time. Our model showed a good agreement with the measured copper mass in each part for all tested conditions with an elapsed time (R² for P. subcapitata: 0.928, R² for C. vulgaris: 0.943). This study provides a novel kinetic dynamics model that is compromised between practical simplicity and realistic complexity, and it can be used to investigate the chronic effects of heavy metals on the algal population.

• Food Science of Animal Resources
• /
• v.41 no.2
• /
• pp.288-299
• /
• 2021

Biofilm formation of Geobacillus thermodenitrificans, Geobacillus thermoglucosidans and Anoxybacillus flavithermus in milk on stainless steel were monitored at 55℃, 60℃, and 65℃ for various incubation times. Although species of Geobacillus showed a rapid response and produced biofilm within 4 h on stainless steel, a delay (lag time) was observed for Anoxybacillus. A hyperbolic equation and a hyperbolic equation with lag could be used to describe the biofilm formation of Geobacillus and Anoxybacillus, respectively. The highest biofilm formation amount was obtained at 60℃ for both Geobacillus and Anoxybacillus. However, the biofilm formation rates indicated that the lowest rates of formation were obtained at 60℃ for Geobacillus. Moreover, biofilm formation rates of G. thermodenitrificans (1.2-1.6 Log10CFU/mL∙h) were higher than G. thermoglucosidans (0.4-0.7 Log10CFU/mL∙h). Although A. flavithermus had the highest formation rate values (2.7-3.6 Log10CFU/mL∙h), this was attained after the lag period (4 or 5 h). This study revealed that modeling could be used to describe the biofilm formation of thermophilic bacilli in milk.

• Applied Chemistry for Engineering
• /
• v.9 no.6
• /
• pp.889-893
• /
• 1998

In this research, mathematical models for predicting the shelf life of packaged tofu in a polyethylene container were developed. Transfer of oxygen in air through the package and then diffusion of oxygen into the filled water and the tofu with the simultaneous oxygen consumption by micoorganisms were studied. The results of simulation showed that the increase of microorganisms in the filled water was more than that in tofu. As a result, it turns out that the shelf life of packaged tofu was not determined by the number of microorganisms in the tofu, but by that in the filled water. Additionally, the effects of physical properties of packaging material and packaged materials, such as the oxygen permeability of packaging material, oxygen diffusion coefficient and the initial oxygen concentration in filled water, and the depth of the filled water, on the shelf life of packaged tofu, were observed.

• Journal of Microbiology and Biotechnology
• /
• v.33 no.9
• /
• pp.1238-1249
• /
• 2023

In this study, we sought to investigate the production and optimization of biosurfactants by soil fungi isolated from petroleum oil-contaminated soil in Saudi Arabia. Forty-four fungal isolates were isolated from ten petroleum oil-contaminated soil samples. All isolates were identified using the internal transcribed spacer (ITS) region, and biosurfactant screening showed that thirty-nine of the isolates were positive. Aspergillus niger SA1 was the highest biosurfactant producer, demonstrating surface tension, drop collapsing, oil displacement, and an emulsification index (E₂₄) of 35.8 mN/m, 0.55 cm, 6.7 cm, and 70%, respectively. This isolate was therefore selected for biosurfactant optimization using the Fit Group model. The biosurfactant yield was increased 1.22 times higher than in the nonoptimized medium (8.02 g/l) under conditions of pH 6, temperature 35℃, waste frying oil (5.5 g), agitation rate of 200 rpm, and an incubation period of 7 days. Model significance and fitness analysis had an RMSE score of 0.852 and a p-value of 0.0016. The biosurfactant activities were surface tension (35.8 mN/m), drop collapsing (0.7 cm), oil displacement (4.5 cm), and E₂₄ (65.0%). The time course of biosurfactant production was a growth-associated phase. The main outputs of the mathematical model for biomass yield were Yx/s (1.18), and µ_max (0.0306) for biosurfactant yield was Y_p/s (1.87) and Y_p/x (2.51); for waste frying oil consumption the So was 55 g/l, and Ke was 2.56. To verify the model's accuracy, percentage errors between biomass and biosurfactant yields were determined by experimental work and calculated using model equations. The average error of biomass yield was 2.68%, and the average error percentage of biosurfactant yield was 3.39%.

• Journal of Physiology & Pathology in Korean Medicine
• /
• v.21 no.1
• /
• pp.82-85
• /
• 2007

The Chinese medicinal plant Artemisia annua is the source of the antimalarial compound artemisinin. By the way, Artemisin annula was known have endoperoxide ring structure is included and has anti-malarial effect. Malaria and Toxoplasma gondii (T. gondii) is belong to Apicomplexa genera. So, confirmed whether we go compound 1,5-bis(4-methoxyphenyl)-6,7-dioxa-bicyclo[3.2.2]nonane that have endoperoxide ring structure and there is anti-toxoplasmosis effect. The efficacy of 1,5-bis(4-methoxyphenyl)-6,7-dioxa-bicyclo[3.2.2] nonane alone was examined in vitro and in a murine model of acute toxoplasmosis. In vitro studies were peformed with HeLa cell cultures, with quantification of Toxoplasma growth by a cell proliferation assay. Selectivity of 1,5-bis(4-methoxyphenyl)-6,7-dioxa-bicyclo[3.2.2]nonane was 4.9 in vitro cell proliferation assay, this is higher than sulfadiazine (selectivity was 1.63). For in vivo studies, mice were acutely infected intraperitoneally with 10$^5$ tachyzoites of the virulent RH strain and then treated perorally for 4 days from 6 hours postinfection. Efficacy was assessed by sequential determination of parasite burdens in peritoneal cavity. in vitro, 1,5-bis(4-methoxyphenyl)-6,7-dioxa-bicyclo[3.2.2]nonane inhibited Toxoplasma growth at a concentration of 150mg/kg of body weight per day, the inhibition ratio was estimated to be 85.72%.

• Asian-Australasian Journal of Animal Sciences
• /
• v.33 no.3
• /
• pp.408-415
• /
• 2020

Objective: The aim of the paper was to compare the fit of data derived from daily automatic milking systems (AMS) and monthly test-day records with the use of lactation curves; data was analysed separately for primiparas and multiparas. Methods: The study was carried out on three Polish Holstein-Friesians (PHF) dairy herds. The farms were equipped with an automatic milking system which provided information on milking performance throughout lactation. Once a month cows were also subjected to test-day milkings (method A4). Most studies described in the literature are based on test-day data; therefore, we aimed to compare models based on both test-day and AMS data to determine which mathematical model (Wood or Wilmink) would be the better fit. Results: Results show that lactation curves constructed from data derived from the AMS were better adjusted to the actual milk yield (MY) data regardless of the lactation number and model. Also, we found that the Wilmink model may be a better fit for modelling the lactation curve of PHF cows milked by an AMS as it had the lowest values of Akaike information criterion, Bayesian information criterion, mean square error, the highest coefficient of determination values, and was more accurate in estimating MY than the Wood model. Although both models underestimated peak MY, mean, and total MY, the Wilmink model was closer to the real values. Conclusion: Models of lactation curves may have an economic impact and may be helpful in terms of herd management and decision-making as they assist in forecasting MY at any moment of lactation. Also, data obtained from modelling can help with monitoring milk performance of each cow, diet planning, as well as monitoring the health of the cow.

• Journal of applied mathematics & informatics
• /
• v.26 no.1_2
• /
• pp.355-364
• /
• 2008

Under pathological stress stimuli, dynamics of a biological system can be changed by alteration of several components such as functional proteins, ultimately leading to disease state. These dynamics in disease state can be modeled using differential equations in which kinetic or system parameters can be obtained from experimental data. One of the most effective ways to restore a particular disease state of biology system (i.e., cell, organ and organism) into the normal state makes optimization of the altered components usually represented by system parameters in the differential equations. There has been no such approach as far as we know. Here we show this approach with a cardiac hypertrophy model in which we obtain the existence of the optimal parameters and construct an optimal system which can be used to find the optimal parameters.

• Proceedings of the Korean Society for Bioinformatics Conference
• /
• 2005.09a
• /
• pp.191-196
• /
• 2005

Genetic networks are a key to unraveling dynamic properties of biological processes and regulation of genes plays an essential role in dynamic behavior of the genetic networks. A popular characterization of regulation of the gene is a kinetic model. However, many kinetic parameters in the genetic regulation have not been available. To overcome this difficulty, in this report, state-space approach to modeling gene regulation is presented. Second-order systems are used to characterize gene regulation. Interpretation of coefficients in the second order systems as resistance, capacitance and inductance is studied. The mathematical methods for transient response analysis of gene regulation to external perturbation are investigated. Criterion for classifying gene into three categories: underdamped, overdamped and critical damped is discussed. The proposed models are applied to yeast cell cycle gene expression data.

• Proceedings of the Korean Society for Bioinformatics Conference
• /
• 2004.11a
• /
• pp.50-56
• /
• 2004

Bifurcation analysis of cell cycle regulation in the budding yeast is performed basedon the mathematical model by Chen et al [Molecular biology of cell, 11:369-391, 2000]. On the bifurcation diagram, locations of both stable and unstable solutions of the nonlinear differential equations are presented by taking the mass of cell as a controlparameter. Based on the bifurcation diagram, dynamic mechanism underlying the 'start' transition, initiation of a new round of cell cycle, and the 'finish' transition, completion of cell cycle and returning back to the initial state, is discussed: the 'start' transition is a transition from a stable fixed solution for a small mass and to an oscillatory state for a large mass, and the 'finish' transition is a switching back to the stable fixed solution from the oscillatory state. To understand the role of the genes during the cell cycle regulation, bifurcation diagrams for the mutants are compared with that of the wild type.