ABSTRACT
El monitoreo del contenido de humedad en el suelo es especialmente importante, ya que proporciona información relevante para tomar decisiones acertadas, en cuanto a riego, fertirriego y manejo del estrés hídrico. Este trabajo tiene como objetivo validar un modelo de estimación del contenido de agua en el suelo, mediante espectroscopía de reflectancia difusa en el rango del infrarrojo cercano. Los suelos evaluados provienen de los municipios de Puerto Gaitán (Meta), Espinal (Tolima) y Mosquera (Cundinamarca). En los dos primeros se establecieron redes rígidas, para seleccionar los puntos de muestreo y empleando dos profundidades en cada caso (0-10 y 10-30; 0-10 y 10-25 cm, respectivamente). Para el tercero, se describieron 77 calicatas y se tomaron muestras a 0-10 y 10-35 cm de profundidad. Posteriormente, se evaluó el contenido de humedad considerando 0, 15 y 30 % de humedad. Los datos obtenidos se analizaron con estadística descriptiva. Se empleó la validación cruzada y externa para cada modelo y se obtuvo un modelo general, a partir de los datos de los tres sitios. Los modelos obtenidos para cada sitio de muestreo y el modelo general tienen buena capacidad predictiva. Según los resultados, se afirma que la espectroscopía de reflectancia difusa NIR es una excelente opción para determinar el contenido de agua en el suelo. De igual manera, a partir del análisis de componentes principales, se identificó una diferenciación entre contenidos de agua de los suelos estudiados.
Monitoring soil moisture content is especially important as it provides relevant information for making informed decisions regarding irrigation, fertigation, and water stress management. This study aims to validate a model for estimating soil water content using diffuse reflectance spectroscopy in the near-infrared range. The evaluated soils come from the municipalities of Puerto Gaitán (Meta), Espinal (Tolima), and Mosquera (Cundinamarca). In the first two municipalities, rigid networks were established to select sampling points, with two depths considered for each case (0-10 and 10-30 cm; 0-10 and 10-25 cm, respectively). For the third municipality, 77 soil pits were described, and samples were taken at depths of 0-10 and 10-35 cm. Subsequently, moisture content was evaluated at 0, 15, and 30 % moisture levels. The obtained data were analyzed using descriptive statistics. Cross-validation and external validation were applied to each model, and a general model was developed based on the data from all three sites. The obtained models for each sampling site and the general model demonstrated good predictive capacity. Based on the results, it is affirmed that near-infrared diffuse reflectance spectroscopy is an excellent option for determining soil water content. Similarly, principal component analysis identified differentiation between water contents of the studied soils.
ABSTRACT
OBJECTIVE To establish the estimation model for the exposure of mycophenolic acid （MPA） in early renal transplant recipients [calculated by the area under the plasma concentration-time curve with 12 h （AUC0－12 h）]. METHODS Twenty kidney transplant recipients， who received triple immunosuppressive therapy of mycophenolate mofetil （MMF）+tacrolimus+ methylprednisolone， were selected and given MMF dispersible tablets （750 mg， q12 h） on the 15th day after the operation； the blood samples were collected from the patients before and 0.5， 1.0， 1.5， 2.0， 3.0， 4.0， 6.0， 8.0， 12.0 hours after the administration， respectively. The blood concentration of MPA was determined， and the pharmacokinetic parameters of MPA were calculated. The multivariate linear stepwise regression analysis method was used to fit an estimation formula for the finite sampling method suitable for MPA-AUC0－12 h of the recipients. Bland-Altman analysis was used to evaluate the agreement between the estimation formula and the classical pharmacokinetic method. RESULTS The main pharmacokinetic parameters of MPA in 20 renal transplant recipients： c0 was （1.53±0.84） μg/mL， cmax was （12.07±5.97） μg/mL， t1/2 was （5.41±3.67） h， tmax was （1.58±0.75） h， and the average AUC0－12 h calculated by the classical pharmacokinetic method was （33.95±13.40） μg·h/mL. MPA-AUC0－12 h was estimated with sampling points of “4.0， 8.0， 12.0 h”； the simplified calculation formula was AUC0－12 h＝12.058+2.819c4.0+7.045c8.0+ 3.879c12.0 （R 2＝0.934）. The predicted value had a good correlation and consistency with the measured value， and 95.0% of predicted values did not exceed the x±1.96SD （standard deviation） range. CONCLUSIONS The estimation model is established successfully for the exposure of MPA in early renal transplant recipients； the model has better prediction accuracy and fewer sampling points.
ABSTRACT
Objective@#To obtain precise data on the changes in the levels of 29 cytokines in mice after high or low linear energy transfer (LET) irradiation and to develop an accurate model of radiation exposure based on the cytokine levels after irradiation.@*Methods@#Plasma samples harvested from mice at different time points after carbon-ion or X-ray irradiation were analyzed using meso-scale discovery (MSD), a high-throughput and sensitive electrochemiluminescence measurement technique. Dose estimation equations were set up using multiple linear regression analysis.@*Results@#The relative levels of IL-6 at 1 h, IL-5 and IL-6 at 24 h, and IL-5, IL-6 and IL-15 at 7 d after irradiation with two intensities increased dose-dependently. The minimum measured levels of IL-5, IL-6 and IL-15 were up to 4.0076 pg/mL, 16.4538 pg/mL and 0.4150 pg/mL, respectively. In addition, dose estimation models were established and verified.@*Conclusions@#The MSD assay can provide more accurate data regarding the changes in the levels of the cytokines IL-5, IL-6 and IL-15. These cytokines could meet the essential criteria for radiosensitive biomarkers and can be used as radiation indicators. Our prediction models can conveniently and accurately estimate the exposure dose in irradiated organism.
Subject(s)
Animals , Female , Mice , Biological Assay , Biomarkers/blood , Carbon , Cytokines/blood , Heavy Ions , Linear Energy Transfer , Linear Models , Radiation Dosage , Radiation, IonizingABSTRACT
The purpose in this study is to make a regression model for the prediction of skeletal muscle volume in thigh. For this purpose, men,14 and women,6 were included in this study. They were measured 22 independent variables by CT and anthropometry methods. CT Image analysis were performed with INFINITT, Rapidia 2.8, Korea. The results in this study are as following. There were not significant (P=.000) between CT-measured variables and predicted variables by anthropometry, excepting the difference (P=0.01) at thigh top muscle circumference. Therefore, many of variables could be applied with parameters for estimation equation by anthropometry. The estimation equation, obtained for thigh muscle volume using the predicted mid-thigh muscle circumference corrected by skinfold thickness and predicted total femur bone volume, was Y(Mtot)=127.4134x(X1)+18.7767x(X2)-5998.62. Where, X1 is predicted mid-thigh muscle circumference and X2 is predicted total femur bone volume. R2 in this model is .97, and SEE is 123 mL, CV 3.6%. In conclusion, the determination of skeletal muscle volume in thigh can be highly validated with estimaton model in this study. Therefore it also be apply to predicting thigh muscle volume in korean adults.