The geochemistry and isotopic compositions of the Nakdong River, Korea: weathering and anthropogenic effects.

The Nakdong River is the longest river in South Korea, and flows through various geological terrains with different land use characteristics; therefore, the geochemistry of its water is expected to be influenced by many factors. In this work, the geochemical characteristics of the Nakdong River were examined, and its chemical compositions, δD, δ18O, and δ13CDIC values, and 87Sr/86Sr ratios were determined to investigate the geological and anthropogenic effects on the geochemistry of the Nakdong River water. The obtained concentrations of major ions were strongly affected by both the anthropogenic activity and weathering of the rocks. With increasing the flow distance, the ion concentrations slightly increased; and after the inflow of the Kumho River, which was the largest tributary running through Daegu (the fourth largest city in South Korea), the concentrations of Na and SO4 ions abruptly increased and decreased again, suggesting the existence of strong anthropogenic effects caused by sewage treatment plants and dyeing industrial complex. Other activities such as agricultural ones also increased the NO3 concentration. In July, the high precipitation level from tropical cyclones and downpours decreased the ion concentrations as well as the δD and δ18O values. The δ13CDIC magnitudes showed that the dissolved inorganic carbon mainly originated from mineral weathering upstream, while the oxidation of soil organic materials influenced by agricultural activity became more important downstream. The 87Sr/86Sr ratios revealed that in the upstream regions, the weathering of granite and gneiss complex was dominant, while in the downstream regions, the weathering of sedimentary rocks became more important. The weathering and anthropogenic effects on the river water chemistry were also demonstrated using statistical analysis, which revealed that the water geochemistry was mostly influenced by the anthropogenic sources, including industrial complex, represented by Na, Cl, and SO4. The obtained results show that, as compared to the geochemistry of the Han River (which is also a major river in Korea), the geochemistry of the Nakdong River is more influenced by anthropogenic activities (including agriculture and the industrial complex) due to the different land use.

Pharmacokinetic properties of isosorbide-5-mononitrate under fasting and fed conditions in healthy male subjects.

OBJECTIVE: This study was performed to compare the pharmacokinetic properties and relative bioavailability of two isosorbide-5-mononitrate (5-ISMN) sustained-release drugs in healthy Korean subjects under fasting and fed conditions. METHODS: A total of 60 healthy volunteers (30 each in the fasting and fed arms of the study) were enrolled in the study and were randomized to treatment. After the administration of a single dose of one of the investigational products, blood samples were collected at specific time intervals from 0 to 36 hours. The plasma concentrations of 5-ISMN were measured by LC-MS/MS. The pharmacokinetic parameters were calculated, and the 90% confidence intervals (CIs) of the geometric mean ratio (test/reference) of the parameters were obtained by analysis of variance on logarithmically transformed data. RESULTS: The corresponding 90% CIs of AUClast and Cmax for the test/reference geometric mean ratio were 90.75 - 98.44% and 92.28 - 98.33%, respectively, under fasting conditions. In the fed state study, the 90% CIs for the geometric mean ratio of test to reference drugs were 94.79 - 103.33% for AUClast and 99.86 - 108.02% for Cmax. CONCLUSION: The test product is equivalent to the reference product in subjects under fasting and fed conditions within the Korean regulatory bioequivalence criteria. Both formulations were safe and well tolerated, and there were no noteworthy differences in the safety profiles between the test and reference drugs.

Relationship between objectively measured lifestyle factors and health factors in patients with knee osteoarthritis: The STROBE Study.

The purpose of this study was to investigate the association between objectively-measured lifestyle factors and health factors in patients with knee osteoarthritis (OA).In this cross-sectional study, 52 patients with knee OA were examined. Lifestyle factors were measured using a wearable smartwatch (step counts, walking distance, calorie consumption, sleep hours) and by self-report (eating speed). Body mass index (BMI), waist circumference, blood pressure, muscle strength of knee extensor and hip abductor, knee pain, symptoms, daily living function, sports recreation function, quality of life by knee injury and OA outcome score (KOOS) were measured to obtain data on health factors. Correlations and regression analysis were used to analyze the relationship between lifestyle factors and health factors.KOOS subscales (pain, symptom, daily living function) and hip abductor strength were positively correlated with daily step count, which was the only independently contributing lifestyle factor. Additionally, knee pain duration and diastolic blood pressure were negatively correlated with daily step count. BMI and waist circumference showed no correlation with physical activity data, but were negatively correlated with sleep duration and eating speed.The findings of this study contribute to expanding the knowledge on how lifestyle habits of older patients with knee OA contribute to their health status. Daily step counts were associated with knee OA-related pain, symptom, function in daily living, duration of knee pain, blood pressure, and strength of hip abductor. BMI and waist circumference were associated with sleep duration and eating speed.

A predictive estimation method for carbon dioxide transport by data-driven modeling with a physically-based data model.

In this study, a data-driven method for predicting CO2 leaks and associated concentrations from geological CO2 sequestration is developed. Several candidate models are compared based on their reproducibility and predictive capability for CO2 concentration measurements from the Environment Impact Evaluation Test (EIT) site in Korea. Based on the data mining results, a one-dimensional solution of the advective-dispersive equation for steady flow (i.e., Ogata-Banks solution) is found to be most representative for the test data, and this model is adopted as the data model for the developed method. In the validation step, the method is applied to estimate future CO2 concentrations with the reference estimation by the Ogata-Banks solution, where a part of earlier data is used as the training dataset. From the analysis, it is found that the ensemble mean of multiple estimations based on the developed method shows high prediction accuracy relative to the reference estimation. In addition, the majority of the data to be predicted are included in the proposed quantile interval, which suggests adequate representation of the uncertainty by the developed method. Therefore, the incorporation of a reasonable physically-based data model enhances the prediction capability of the data-driven model. The proposed method is not confined to estimations of CO2 concentration and may be applied to various real-time monitoring data from subsurface sites to develop automated control, management or decision-making systems.