A seamless approach to understanding and predicting Arctic sea ice in Met Office modelling systems.

Recent CMIP5 models predict large losses of summer Arctic sea ice, with only mitigation scenarios showing sustainable summer ice. Sea ice is inherently part of the climate system, and heat fluxes affecting sea ice can be small residuals of much larger air-sea fluxes. We discuss analysis of energy budgets in the Met Office climate models which point to the importance of early summer processes (such as clouds and meltponds) in determining both the seasonal cycle and the trend in ice decline.

Potentiation of tumor responses to DNA damaging therapy by the selective ATR inhibitor VX-970.

Platinum-based DNA-damaging chemotherapy is standard-of-care for most patients with lung cancer but outcomes remain poor. This has been attributed, in part, to the highly effective repair network known as the DNA-damage response (DDR). ATR kinase is a critical regulator of this pathway, and its inhibition has been shown to sensitize some cancer, but not normal, cells in vitro to DNA damaging agents.

Gene expression studies for the analysis of domoic acid production in the marine diatom Pseudo-nitzschia multiseries.

Background: Pseudo-nitzschia multiseries Hasle (Hasle) (Ps-n) is distinctive among the ecologically important marine diatoms because it produces the neurotoxin domoic acid. Although the biology of Ps-n has been investigated intensely, the characterization of the genes and biochemical pathways leading to domoic acid biosynthesis has been limited. To identify transcripts whose levels correlate with domoic acid production, we analyzed Ps-n under conditions of high and low domoic acid production by cDNA microarray technology and reverse-transcription quantitative PCR (RT-qPCR) methods.

Standardizing global gene expression analysis between laboratories and across platforms.

To facilitate collaborative research efforts between multi-investigator teams using DNA microarrays, we identified sources of error and data variability between laboratories and across microarray platforms, and methods to accommodate this variability. RNA expression data were generated in seven laboratories, which compared two standard RNA samples using 12 microarray platforms. At least two standard microarray types (one spotted, one commercial) were used by all laboratories.