Citations

Background and aim Although Non-steroidal anti-inflammatory drugs reduce colorectal adenoma burden in familial adenomatous polyposis (FAP), the utility of combining chemopreventive agents in FAP is not known. We conducted a randomised trial of celecoxib (CXB) versus CXB+diflouromethylornithine (DFMO) to determine the synergistic effect, if any. Methods The primary endpoint was % change in adenoma count in a defined field. Secondary endpoints were adenoma burden (weighted by adenoma diameter) and video review of entire colon/rectal segments. Adverse event (AEs) were monitored by National Cancer Institution toxicity criteria. Results 112 subjects were randomised: 60 men and 52 women at a mean age of 38 years. For the 89 patients who had landmark-matched polyp counts available at baseline and 6 months, the mean % change in adenoma count over the 6 months of trial was −13.0% for CXB+DFMO and −1.0% for CXB (p=0.69). Mean % change in adenoma burden was −40% (CXB+DFMO) vs −27% (CXB) (p=0.13). Video-based global polyp change was −0.80 for CXB+DFMO vs −0.33 for CXB (p=0.03). Fatigue was the only significant AE, worse on the CXB arm (p=0.02). Conclusions CXB combined with DFMO yielded moderate synergy according to a video-based global assessment. No significant difference in adenoma count, the primary endpoint, was seen between the two study arms. No evidence of DFMO-related ototoxicity was seen. There were no adverse cardiovascular outcomes in either trial arm and no significant increase in AEs in the CXB+DFMO arm of the trial. Differences in outcomes between primary and secondary endpoints may relate to sensitivity of the endpoint measures themselves. Trial registration number ClinicalTrials.gov number N01-CN95040.

Background— There is a paucity of data on the use of optimal medical therapy (OMT) in patients with complex coronary artery disease undergoing revascularization with percutaneous coronary intervention or coronary artery bypass grafting (CABG) and its long-term prognostic significance. Methods and Results— The Synergy Between Percutaneous Coronary Intervention With TAXUS and Cardiac Surgery (SYNTAX) trial is a multicenter, randomized, clinical trial of patients (n=1800) with complex coronary disease randomized to revascularization with percutaneous coronary intervention or CABG. Detailed drug history was collected for all patients at discharge and at the 1-month, 6-month, 1-year, 3-year, and 5-year follow-ups. OMT was defined as the combination of at least 1 antiplatelet drug, statin, β-blocker, and angiotensin-converting enzyme inhibitor/angiotensin receptor blocker. Five-year clinical outcomes were stratified by OMT and non-OMT. OMT was underused in patients treated with coronary revascularization, especially CABG. OMT was an independent predictor of survival. OMT was associated with a significant reduction in mortality (hazard ratio, 0.64; 95% confidence interval, 0.48–0.85; P =0.002) and composite end point of death/myocardial infarction/stroke (hazard ratio, 0.73; 95% confidence interval, 0.58–0.92; P =0.007) at the 5-year follow-up. The treatment effect with OMT (36% relative reduction in mortality over 5 years) was greater than the treatment effect of revascularization strategy (26% relative reduction in mortality with CABG versus percutaneous coronary intervention over 5 years). On stratified analysis, all the components of OMT were important for reducing adverse outcomes regardless of revascularization strategy. Conclusions— The use of OMT remains low in patients with complex coronary disease requiring coronary intervention with percutaneous coronary intervention and even lower in patients treated with CABG. Lack of OMT is associated with adverse clinical outcomes. Targeted strategies to improve OMT use in postrevascularization patients are warranted. Clinical Trial Registration— URL: http://www.clinicaltrials.gov . Unique identifier: NCT00114972.

Circadian rhythm dysfunction is linked to many diseases, yet pathophysiological roles in articular cartilage homeostasis and degenerative joint disease including osteoarthritis (OA) remains to be investigated in vivo. Here, we tested whether environmental or genetic disruption of circadian homeostasis predisposes to OA‐like pathological changes. Male mice were examined for circadian locomotor activity upon changes in the light:dark (LD) cycle or genetic disruption of circadian rhythms. Wild‐type (WT) mice were maintained on a constant 12 h:12 h LD cycle (12:12 LD) or exposed to weekly 12 h phase shifts. Alternatively, male circadian mutant mice ( Clock Δ19 or Csnk1e tau mutants) were compared with age‐matched WT littermates that were maintained on a constant 12:12 LD cycle. Disruption of circadian rhythms promoted osteoarthritic changes by suppressing proteoglycan accumulation, upregulating matrix‐degrading enzymes and downregulating anabolic mediators in the mouse knee joint. Mechanistically, these effects involved activation of the PKCδ‐ERK‐RUNX2/NFκB and β‐catenin signaling pathways, stimulation of MMP‐13 and ADAMTS‐5, as well as suppression of the anabolic mediators SOX9 and TIMP‐3 in articular chondrocytes of phase‐shifted mice. Genetic disruption of circadian homeostasis does not predispose to OA‐like pathological changes in joints. Our results, for the first time, provide compelling in vivo evidence that environmental disruption of circadian rhythms is a risk factor for the development of OA‐like pathological changes in the mouse knee joint. J. Cell. Physiol. 230: 2174–2183, 2015. © 2015 Wiley Periodicals, Inc.

Classic multinomial logit model, commonly used in multiclass regression problem, is restricted to few predictors and does not take into account the relationship among variables. It has limited use for genomic data, where the number of genomic features far exceeds the sample size. Genomic features such as gene expressions are usually related by an underlying biological network. Efficient use of the network information is important to improve classification performance as well as the biological interpretability. We proposed a multinomial logit model that is capable of addressing both the high dimensionality of predictors and the underlying network information. Group lasso was used to induce model sparsity, and a network-constraint was imposed to induce the smoothness of the coefficients with respect to the underlying network structure. To deal with the non-smoothness of the objective function in optimization, we developed a proximal gradient algorithm for efficient computation. The proposed model was compared to models with no prior structure information in both simulations and a problem of cancer subtype prediction with real TCGA (the cancer genome atlas) gene expression data. The network-constrained mode outperformed the traditional ones in both cases.