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The potential of single date fully Polarimetric RADARSAT‐2 data in retrieving crop biophysical parameters using Machine Learning techniques was investigated. Various polarimetric parameters along with coherent and incoherent decomposition techniques were assessed for its sensitivity toward crop parameters like Wet and Dry Biomass, Crop Height, Leaf Area Index and Vegetation Water Content. A set of 39 polarimetric observables extracted from the Quad‐Pol data were used for regression analysis. In this study two Machine Learning techniques Random Forest Regression (RFR) and Multiple Linear Regression (MLR) models were assessed for the prediction of Wet Biomass (gm−2) and Height (cm). The most significant (6 out of 39) variables were applied for prediction. The results revealed that RFR algorithm performed better than MLR. The coefficient of determination (R2) and root‐mean‐square‐error of estimating wet biomass and height were 0.646, 655.65 (gm−2) and 0.71, 14.5 (cm) respectively in RFR and 0.566, 683.86 (gm−2) and 0.65, 16.14 (cm) respectively in MLR. Thus this study explored the effective application of quad‐pol data for assessing sensitivity and accurate retrieval of parameters using optimum PolSAR observables. Key Points: Important polarimetric observables and their sensitivity toward biophysical parameters were analyzedEffective retrieval of crop parameters from a single‐date polarimetric data using Random Forest and Multiple Linear Regression was explored [ABSTRACT FROM AUTHOR]

Apolipoprotein E (ApoE) has been associated with several diseases including Parkinson's disease, Alzheimer's and multiple sclerosis. ApoE also has documented immunomodulatory functions. We investigated gene expression in circulating monocytes and in bone marrows of patients with visceral leishmaniasis (VL) living in an endemic area in Bihar, India, and contrasted these with control healthy subjects or other diagnostic bone marrows from individuals in the same region. Samples from VL patients were obtained prior to initiating treatment. Our study revealed significant upregulated expression of the apoE transcript in patients with VL. Furthermore, the levels of ApoE protein were elevated in serum samples of subjects with VL compared with healthy endemic controls. These observations may provide clues regarding the complex interactions between lipid metabolism and immunoregulation of infectious and inflammatory diseases. [ABSTRACT FROM AUTHOR]