Abstract. It is common to measure a large number of features in parallel to identify those differing between two experimental conditions -e.g. the search for differentially expressed genes using microarrays or RNA-Seq. Ranking features by p-value allows for control of the TYPE I error, but p-values are not reliable when there are very few replicates; and investigators typically require features be ranked by "fold change"x/ȳ in conjunction with p-values. At first glance the fold change appears to be a natural quantity on which to compare the differential behavior of features. But it is highly sensitive to small values in the denominator and is problematic in how it equates changes in both small and large numbers such as a change from 1 to 2 versus a change from 100 to 200. The strategy of adjusting all values by adding one is a widely used heuristic approach to try to mitigate the problems with fold-change. However, that can be far from optimal. A systematic strategy to determine an optimal value (pseudocount) to adjust by is employed using both real and simulated benchmark data. In RNA-Seq a value of 20 appears to be close to optimal in all cases. Another strategy is to sort by differenceȳ −x, but this is problematic for comparing measurements across a wide spectum, as large differences of small values rank below proportionally smaller difference in large values. An abstract mathematical framework is introduced to describe the problem of ranking by differential effect size, enabling us to study the ranking problem in general as opposed to specific contexts such as fold-change or difference. From this framework we discovered a remarkable property of pseudocounts, in that they strike a balance between sorting by fold-change and sorting by difference. Lastly, another fundamentally different type of application is presented, which is to rank di-codons by their differential abundance in the ORFeome of different species.

Nonsteroidal anti-inflammatory drugs (NSAIDs) relieve inflammatory pain by predominant suppression of cyclooxygenase-2 derived prostaglandin (PG) E2. Innate immune cells contribute to inflammatory pain hypersensitivity and may be an attractive target for novel non-addictive approaches to pain management. We studied the contribution of PGE2 produced by myeloid cell microsomal prostaglandin E synthase -1 (mPGES-1) to peripheral inflammation and hyperalgesia in mice. Selective deletion of mPGES-1 in myeloid cells by crossing LysM-Cre mice with mPGES-1flox/flox mice (Mac-mPGES-1-KO) resulted in significantly reduced mechanical and thermal hyperalgesia in complete Freund's adjuvant (CFA)-evoked hind paw inflammation, zymosan-induced peri-articular inflammation and collagen II antibody-induced arthritis models. Systemic COX-2 inhibition or myeloid cell specific COX-2 deletion (by crossing LysM-Cre with COX-2 flox/flox mice) recapitulated reduction of CFA-induced inflammation and hyperalgesia. In contrast, deletion of mPGES-1 in neurons and glial cells by crossing mPGES-1flox/flox mice with Nestin-Cre mice had no detectable effect on inflammatory pain hypersensitivity. While macrophage recruitment was unaltered, tissue concentrations of PGE2, IL-1β and TNFα were significantly reduced in Mac-mPGES-1-KO paw tissues following CFA induction. Our results demonstrate that myeloid cell mPGES-1 is the dominant source of PGE2 in inflammatory pain hypersensitivity. Targeting myeloid cell mPGES-1 may afford a novel approach to inflammatory pain therapy.

Purpose. The cardiovascular biology of proton radiotherapy is not well understood. We aimed to compare the genomic dose-response to proton and gamma radiation of the mouse aorta to assess whether their vascular effects may diverge. Materials and methods.We performed comparative RNA sequencing of the aorta following (4 hrs) total-body proton and gamma irradiation (0.5 -200 cGy whole body dose, 10 dose levels) of conscious mice. A trend analysis identified genes that showed a dose response.Results. While fewer genes were dose-responsive to proton than gamma radiation (29 vs. 194 genes; q-value ≤ 0.1), the magnitude of the effect was greater. Highly responsive genes were enriched for radiation response pathways (DNA damage, apoptosis, cellular stress and inflammation; p-value ≤ 0.01). Gamma, but not proton radiation induced additionally genes in vasculature specific pathways. Genes responsive to both radiation types showed almost perfectly superimposable dose-response relationships. Conclusions.Despite the activation of canonical radiation response pathways by both radiation types, we detected marked differences in the genomic response of the murine aorta. Models of cardiovascular risk based on photon radiation may not accurately predict the risk associated with proton radiation.

The analgesic efficacy of non-steroidal anti-inflammatory drugs (NSAIDs) has long been recognized to be limited by substantial interindividual variability in pain relief, but the underlying mechanisms are not well understood. We performed pain phenotyping, functional neuroimaging, pharmacokinetic/pharmacodynamic assessments, inflammation biomarkers, and gene expression profiling in healthy subjects who underwent surgical extraction of bony impacted third molars, in order to characterize factors associated with heterogeneity in response to ibuprofen.Subjects were treated with rapid-acting ibuprofen (400 mg; N=19) or placebo (N=10) in a randomized, double-blind design. Compared to placebo, ibuprofen-treated subjects exhibited greater reduction in pain scores, alterations in regional cerebral blood flow in brain regions associated with pain processing, and inhibition of ex vivo cyclooxygenase activity and urinary prostaglandin metabolite excretion as indices of biochemical drug action (p<0.05). As expected, ibuprofen-treated subjects could be stratified into partial responders (N=9, required rescue medication within the dosing interval) and complete responders (N=10, no rescue medication).This was also reflected by differences in pain scores (p<0.01) as early as 30 minutes following drug administration (p<0.05). Variability in analgesic efficacy was not associated with demographic or clinical characteristics, ibuprofen pharmacokinetics, metabolizing enzyme genotype, or the degree of cyclooxygenase inhibition by ibuprofen. However, complete responders had higher concentrations of inflammatory biomarkers in urine and serum, than partial responders. Specifically, a stable urinary prostaglandin E 2 metabolite, serum TNFα and IL-8 were higher in patients who did not require rescue medication compared those who did (p < 0.05). RNAseq gene expression analysis in PBMCs collected after surgery and ibuprofen administration showed enrichment of inflammation related pathways among genes differentially expressed (q < 0.2) between complete and partial responders These findings suggest that patients who receive substantial pain relief from ibuprofen have a more pronounced activation of the prostanoid biosynthetic pathway and regulation of the inflammatory pain phenotype differs from those patients who are insufficiently treated with ibuprofen alone and may require an opioid or other therapeutic intervention.