B-cell receptor (BCR) signaling has been inferred as an important mechanism for disease progression in chronic lymphocytic leukemia (CLL) and other B-cell malignancies. In response to BCR activation, CLL cells secrete the chemokine CCL3, which fosters interactions between CLL cells and the leukemia microenvironment. CCL3 secretion correlates with expression of the 70-kDa ζ-associated protein (ZAP-70) and responsiveness of the CLL clone to BCR stimulation. Here, we measured CCL3 plasma levels by enzyme-linked immunosorbent assay (ELISA) in 351 CLL patients and examined CCL3 levels for associations with established prognostic markers and time from diagnosis to initial therapy. We found that CCL3 plasma concentrations were strongly associated with established prognostic markers. In a Cox proportional hazards regression model, CCL3 as well as established prognostic markers (immunoglobulin heavy chain variable-region mutation status, CD38 or ZAP-70 cytogenetics, clinical stage) were significantly associated with time to treatment. Multivariable analysis revealed that CCL3 (hazard ratio [HR] = 2.33, P < .0001), advanced clinical stage (HR = 2.75, P = .0025), poor risk cytogenetics (del 17p, HR = 2.38; del11q, HR = 2.36, P = .001), and CD38 expression (HR = 1.43, P = .023) were independent prognostic markers. Collectively, CCL3 is a novel, robust, and independent prognostic marker in CLL that can easily and reliably be measured by ELISA. CCL3 therefore should become useful for risk assessment in patients with CLL.

The study of hand samples is a significant aspect of geoscience. This work showcases a technique for relatively quick and inexpensive mineral characterization, applied to a Cretaceous limestone formation and for sulfide-rich quartz vein samples from Northern Pakistan. Spectral feature parameters are derived from mineral mixtures of known abundance and are used for mineral mapping. Additionally, three well-known classification techniques—Spectral Angle Mapper (SAM), Support Vector Machine (SVM), and Neural Network—are compared. Point counting results from petrographic thin sections are used for validation the limestone samples, and QEMSCAN mineral maps for the sulfide samples. For classifying the carbonates, the SVM classifier produced results that are closest to the training set—with 84.4% accuracy and a kappa coefficient of 0.8. For classifying sulfides, SAM produced mineral abundances that were closest to the validation data, possibly due to the low reflectance of sulfides throughout the short-wave infrared spectrum with some differences in the overall spectral shape.

Hydrocarbon microseepage can be detected by its altering effect on rocks, soils, and overlying vegetation. This study examines the impact of hydrocarbon seepage on vegetation. Microseeping hydrocarbons alter soil chemistry, often creating an environment that can impact the health of overlying vegetation; these effects can be observed using remote sensing. Blackburn and Eagle Springs oil fields in Nevada; Patrick Draw and Little Buffalo Basin oil fields in Wyoming; and Cement oil field in Oklahoma were selected for this study because previous investigations confirmed the presence of microseeping hydrocarbons in these locations. In this study, moderate resolution imaging spectroradiometer's (MODIS) monthly average normalized difference vegetation index (NDVI) data from January 2003 to December 2012 were used to observe vegetation health inside oil fields. Average NDVI was calculated for these locations. The typical range of NDVI in desert environments, such as those observed in semi-arid desert environments, can range from 0.18 to 0.49, depending on the season. In Blackburn Oil Field, the averaged NDVI near hydrocarbon production is 0.22, whereas it is 0.23 in areas where production does not occur. In Eagle Springs oil field, the average NDVI is 0.13, while it is 0.22 in surrounding areas. In Patrick Draw, the average NDVI is 0.14 in the oil field versus 0.15 in surrounding areas. In Little Buffalo Basin oil field, the NDVI is 0.19, and it is 0.23 in nearby areas where production does not take place. In Cement, Oklahoma, average NDVI is 0.47 in the oil field and 0.48 outside the oil field. Lower NDVI inside oil fields compared to surrounding areas may indicate lower abundance of vegetation or stressed vegetation, possibly as a result of hydrocarbon seepage and production.