Electrocatalysis for Chemical and Fuel Production: Investigating Climate Change Mitigation Potential and Economic Feasibility.

The manufacture of goods from oil, coal, or gas to everyday consumer products comprises in more or less all cases at least one catalytic step. Compared to conventional hydrothermal catalysis, electrocatalysis possesses the advantage of mild operational conditions and high selectivity, yet the potential energy savings and climate change mitigation have rarely been assessed. This study conducted a life cycle assessment (LCA) for the electrocatalytic oxidation of crude glycerol to produce lactic acid, one of the most common platform chemicals.

Measurement of cell-bound complement activation products enhances diagnostic performance in systemic lupus erythematosus.

Objective: To determine the value of cell-bound complement activation products in combination with antinuclear antibody (ANA), anti-double-stranded DNA antibody (anti-dsDNA), and anti-mutated citrullinated vimentin antibody (anti-MCV) for the diagnosis of systemic lupus erythematosus (SLE).

Methods: This was a multicenter cross-sectional study in which 593 subjects were enrolled (210 SLE patients, 178 patients with other rheumatic diseases, and 205 healthy subjects). Complement receptor 1 levels on erythrocytes (ECR1) together with complement C4d levels on erythrocytes (EC4d), platelets (PC4d), and B cells (BC4d) were determined using fluorescence-activated cell sorting.

Biomarker discovery across annotated and unannotated microarray datasets using semi-supervised learning.

The growing body of DNA microarray data has the potential to advance our understanding of the molecular basis of disease. However annotating microarray datasets with clinically useful information is not always possible, as this often requires access to detailed patient records. In this study we introduce GLAD, a new Semi-Supervised Learning (SSL) method for combining independent annotated datasets and unannotated datasets with the aim of identifying more robust sample classifiers.

Amplification patterns of three genomic regions predict distant recurrence in breast carcinoma.

Currently used clinical and histopathological parameters imprecisely define the risk of distant recurrence in breast cancer, underscoring the need for more informative prognostic markers. In the present fluorescence in situ hybridization study of archived surgical specimens, we derived an algorithm for computing a prognostic index (PI) from DNA copy numbers of three genomic regions (CYP24, PDCD6IP, and BIRC5) for estrogen/progesterone receptor-positive (ER/PR+) cancers and a distinct PI (based on NR1D1, SMARCE1, and BIRC5) for estrogen/progesterone receptor-negative (ER/PR-) cancers. Among independent test cases stratified by PI, recurrence rates were significantly higher among high-risk patients than low-risk patients for both ER/PR+ (odds ratio = 9.