21st century United States emissions mitigation could increase water stress more than the climate change it is mitigating.

There is evidence that warming leads to greater evapotranspiration and surface drying, thus contributing to increasing intensity and duration of drought and implying that mitigation would reduce water stresses. However, understanding the overall impact of climate change mitigation on water resources requires accounting for the second part of the equation, i.e., the impact of mitigation-induced changes in water demands from human activities. By using integrated, high-resolution models of human and natural system processes to understand potential synergies and/or constraints within the climate-energy-water nexus, we show that in the United States, over the course of the 21st century and under one set of consistent socioeconomics, the reductions in water stress from slower rates of climate change resulting from emission mitigation are overwhelmed by the increased water stress from the emissions mitigation itself. The finding that the human dimension outpaces the benefits from mitigating climate change is contradictory to the general perception that climate change mitigation improves water conditions. This research shows the potential for unintended and negative consequences of climate change mitigation.

Bayesian model aggregation for ensemble-based estimates of protein pKa values.

This article investigates an ensemble-based technique called Bayesian Model Averaging (BMA) to improve the performance of protein amino acid pKa predictions. Structure-based pKa calculations play an important role in the mechanistic interpretation of protein structure and are also used to determine a wide range of protein properties. A diverse set of methods currently exist for pKa prediction, ranging from empirical statistical models to ab initio quantum mechanical approaches. However, each of these methods are based on a set of conceptual assumptions that can effect a model's accuracy and generalizability for pKa prediction in complicated biomolecular systems. We use BMA to combine eleven diverse prediction methods that each estimate pKa values of amino acids in staphylococcal nuclease. These methods are based on work conducted for the pKa Cooperative and the pKa measurements are based on experimental work conducted by the García-Moreno lab. Our cross-validation study demonstrates that the aggregated estimate obtained from BMA outperforms all individual prediction methods with improvements ranging from 45 to 73% over other method classes. This study also compares BMA's predictive performance to other ensemble-based techniques and demonstrates that BMA can outperform these approaches with improvements ranging from 27 to 60%. This work illustrates a new possible mechanism for improving the accuracy of pKa prediction and lays the foundation for future work on aggregate models that balance computational cost with prediction accuracy.

One-step conversion of to its using salts for GC-MSdetection of bacterial endospores.

Methyl sulfate (MeSO4-) salts were explored as thermochemolysis-methylation (TCM) reagents for gas chromatographic (GC) analysis of dipicolinic acid (DPA) as its dimethyl ester (Me2DPA) from bacterial endospores. The reaction was carried out under non-pyrolytic conditions by inserting a small coiled wire filament coated with the sample and reagents directly inside a GC injection port at 290 °C. Above 10 : 1 methyl donor/DPA ratios, alkali metal salts of MeSO4- effected 80-90% conversion of DPA to Me2DPA, which was 10-20 times more active than the same amount of tetramethylammonium hydroxide (TMA-OH) at this temperature. A quaternary salt mixture consisting of 1 : 3 : 1 : 3 TMA+/Na+/OH-/MeSO4- methylated spore DPA with an average conversion of 86% (mean conversion by TMA-OH under the same conditions was 4%). Therefore, the sensitivity for detection of bacterial endospores was increased over 20-fold compared to that observed with the more commonly employed TMA-OH methylating reagent. The limit of detection by this method was 9 × 104 total spores. Mechanisms describing the observed behavior are proposed and discussed. This is the first use of MeSO4- as a TCM reagent for GC.

Multi-site assessment of the precision and reproducibility of multiple reaction monitoring-based measurements of proteins in plasma.

Verification of candidate biomarkers relies upon specific, quantitative assays optimized for selective detection of target proteins, and is increasingly viewed as a critical step in the discovery pipeline that bridges unbiased biomarker discovery to preclinical validation. Although individual laboratories have demonstrated that multiple reaction monitoring (MRM) coupled with isotope dilution mass spectrometry can quantify candidate protein biomarkers in plasma, reproducibility and transferability of these assays between laboratories have not been demonstrated. We describe a multilaboratory study to assess reproducibility, recovery, linear dynamic range and limits of detection and quantification of multiplexed, MRM-based assays, conducted by NCI-CPTAC. Using common materials and standardized protocols, we demonstrate that these assays can be highly reproducible within and across laboratories and instrument platforms, and are sensitive to low mug/ml protein concentrations in unfractionated plasma. We provide data and benchmarks against which individual laboratories can compare their performance and evaluate new technologies for biomarker verification in plasma.