Development of agro-climatic grape yield model for Nashik region, Maharashtra, India

Prediction of the crop yield is need of time according to the change in climate conditions. In the present study, the Agro-Climatic Grape Yield (ACGY) model has been developed with monthly climatic parameters using multi-regression analysis approach. The developed model was statistically tested for its predictive ability. The discrepancy ratio, the standard deviation of discrepancy ratio, mean percentage error and standard deviation of mean percentage error for the model was obtained as 1.03, 0.19, 0.03% and 0.19, respectively. Sensitivity analysis was carried out for the developed ACGY model using the parametric sensitivity method. In order to know the future grape yield using ACGY model, climate scenarios were generated under Canadian Earth System Model (CanESM2) for three emissions representative concentration pathways as RCP2.6, RCP4.5, and RCP8.5. According to the analysis using ACGY model, increasing yield was observed in grape up to year 2050 as compared to current yield.

A High-Sensitivity Analysis Method Of Furanocoumarins In Radix Angelicae Dahuricae By Reverse-Phase High-Performance Liquid Chromatography Coupled With Integrated Pulsed Amperometric Detection

Radix Angelicae Dahuricae is a traditional Chinese medicine. We developed a high-sensitivity method for detection of furanocoumarins in Radix Angelicae Dahuricae and Gumiganghwal-tang (GMGHT). The six furanocoumarins of Radix Angelicae Dahuricae were sonication-extracted from 50% ethanol for 60 min. Six furanocoumarins were separated through a gradient elution system. The limits of detection of the components were 0.002–0.3 ng (0.2–30 ng/mL). The coefficients of determination were 0.9995–1.0000, all inter-day and intra-day precision values were < 4.9%, and the mean recoveries and relative standard deviations were 96.4%–104.5% and 0.5%–4.8% for Radix Angelicae Dahuricae extract, respectively. Our method does not require any pretreatment steps and exhibits good reproducibility, selectivity, and sensitivity. Therefore, our method will contribute to a Radix Angelicae Dahuricae quality control measure.

Biodistribution of phenylalanine labeled with gallium-68

Positron emission tomography (PET) is modern high sensitivity method of various tumor imaging. The synthesis of new radiopharmaceuticals based on amino acids and positron emitting radionuclide 68Ga for PET imaging is of great interest. This work is devoted to study the biodistribution of a new agent based on amino acid phenylalanine and 68Ga (68Ga-phenylalanine) in Wistar rats with cholangioma RS-1 after intravenous administration. A comparative investigation of 68Ga-phenylalanine and 68GaCl3 biodistribution was also carried out. It was shown that the highest uptake of 68Ga-phenylalanine was observed in blood, liver, femur and tumor. Tumor uptake of 68Ga-phenylalanine increased 3.5 times from 0.20 ± 0.03 % ID/g to 0.70 ± 0.10 % ID/g, whereas uptake of 68GaCl3 decreased from 0.34 ± 0.07 % ID/g to 0.13 ± 0.04 % ID/g within 3 h. Blood uptake of 68Ga-phenylalanine reached 2.98 ± 0.31 % ID/g. In other organs and tissues the uptake of 68Ga-phenylalanine didn’t exceed 1 % ID/g. Kidneys and femur uptake of 68Ga-phenylalanine was lower as compared with 68GaCl3, but in other organs the uptake of 68Ga-phenylalanine was similar or slightly higher when compared with 68GaCl3.

Minimal Residual Disease in Multiple Myeloma: Something Old, Something New

The game-changing outcome effect, due to the generalized use of novel agents in MM, has cre-ated a paradigm shift. Achieving frequent deep responses has placed MM among those neoplasms where the rationale for assessing MRD is fulfilled. However, its implementation in MM has raised specific questions: how might we weight standard measures against deep MRD in the emerging CAR-T setting? Which high sensitivity method to choose? Are current response criteria still useful? In this work, we address lessons learned from the use of MRD in other neoplasms, the steps followed for the harmonization of current methods for comprehensively measuring MRD, and the challenges that new therapies and concepts pose in the MM clinical field.

Development of agro-climatic grape yield model with future prospective

Agriculture sector is most vulnerable to climate change. To predict the crop yield in accordance with the changing climate is a need of hour than choice. To know the climate in advance is crucial for grape growing farmers and grape export agencies for its better planning and security of grape industries from climate change perspective. In the present study, the Agro-Climatic Grape Yield (ACGY) model is developed on monthly scale climatic parameters using correlation, significance and multi-regression analysis approach. The developed model is statistically tested for its predictive ability. The discrepancy ratio, the standard deviation of discrepancy ratio, mean percentage error and standard deviation of mean percentage error for the developed model is obtained as 1.03, 0.19, 0.03% and 0.19 respectively. Sensitivity analysis is carried out for the developed ACGY model using the parametric sensitivity method. In order to know the grape yield for future using developed ACGY model, climate scenarios are generated under Canadian Earth System Model (CanESM2) for three emissions Representative Concentration Pathways (RCP) as RCP2.6, RCP4.5, and RCP8.5. Model response variability is carried out to understand the variation of grape yield. It is observed that grape yield is showing adverse variation with the increase in minimum temperature in January and November months, and precipitation in August and November months. Whereas, minimum temperature in April and sum of monthly mean evapotranspiration showing accordance effect on the grape yield. It is recommended the use of ACGY model for grape yield estimations applicable for the present and future climate of the study area based on the predictive capability of developed model.