4 resultados para Crossover
em Duke University
Resumo:
PURPOSE: Cutaneous sclerosis occurs in 20% of patients with chronic graft-versus-host disease (GVHD) and can compromise mobility and quality of life. EXPERIMENTAL DESIGN: We conducted a prospective, multicenter, randomized, two-arm phase II crossover trial of imatinib (200 mg daily) or rituximab (375 mg/m(2) i.v. weekly × 4 doses, repeatable after 3 months) for treatment of cutaneous sclerosis diagnosed within 18 months (NCT01309997). The primary endpoint was significant clinical response (SCR) at 6 months, defined as quantitative improvement in skin sclerosis or joint range of motion. Treatment success was defined as SCR at 6 months without crossover, recurrent malignancy or death. Secondary endpoints included changes of B-cell profiles in blood (BAFF levels and cellular subsets), patient-reported outcomes, and histopathology between responders and nonresponders with each therapy. RESULTS: SCR was observed in 9 of 35 [26%; 95% confidence interval (CI); 13%-43%] participants randomized to imatinib and 10 of 37 (27%; 95% CI, 14%-44%) randomized to rituximab. Six (17%; 95% CI, 7%-34%) patients in the imatinib arm and 5 (14%; 95% CI, 5%-29%) in the rituximab arm had treatment success. Higher percentages of activated B cells (CD27(+)) were seen at enrollment in rituximab-treated patients who had treatment success (P = 0.01), but not in imatinib-treated patients. CONCLUSIONS: These results support the need for more effective therapies for cutaneous sclerosis and suggest that activated B cells define a subgroup of patients with cutaneous sclerosis who are more likely to respond to rituximab.
Resumo:
Context : Stress fractures are one of the most common injuries in sports, accounting for approximately 10% of all overuse injuries. Treatment of fifth metatarsal stress fractures involves both surgical and nonsurgical interventions. Fifth metatarsal stress fractures are difficult to treat because of the risks of delayed union, nonunion, and recurrent injuries. Most of these injuries occur during agility tasks, such as those performed in soccer, basketball, and lacrosse. Objective : To examine the effect of a rigid carbon graphite footplate on plantar loading during 2 agility tasks. Design : Crossover study. Setting : Laboratory. Patients or Other Participants : A total of 19 recreational male athletes with no history of lower extremity injury in the past 6 months and no previous metatarsal stress fractures were tested. Main Outcome Measure(s) : Seven 45° side-cut and crossover-cut tasks were completed in a shoe with or without a full-length rigid carbon plate. Testing order between the shoe conditions and the 2 cutting tasks was randomized. Plantar-loading data were recorded using instrumented insoles. Peak pressure, maximum force, force-time integral, and contact area beneath the total foot, the medial and lateral midfoot, and the medial, middle, and lateral forefoot were analyzed. A series of paired t tests was used to examine differences between the footwear conditions (carbon graphite footplate, shod) for both cutting tasks independently (α = .05). Results : During the side-cut task, the footplate increased total foot and lateral midfoot peak pressures while decreasing contact area and lateral midfoot force-time integral. During the crossover-cut task, the footplate increased total foot and lateral midfoot peak pressure and lateral forefoot force-time integral while decreasing total and lateral forefoot contact area. Conclusions : Although a rigid carbon graphite footplate altered some aspects of the plantar- pressure profile during cutting in uninjured participants, it was ineffective in reducing plantar loading beneath the fifth metatarsal.
Resumo:
During mitotic cell cycles, DNA experiences many types of endogenous and exogenous damaging agents that could potentially cause double strand breaks (DSB). In S. cerevisiae, DSBs are primarily repaired by mitotic recombination and as a result, could lead to loss-of-heterozygosity (LOH). Genetic recombination can happen in both meiosis and mitosis. While genome-wide distribution of meiotic recombination events has been intensively studied, mitotic recombination events have not been mapped unbiasedly throughout the genome until recently. Methods for selecting mitotic crossovers and mapping the positions of crossovers have recently been developed in our lab. Our current approach uses a diploid yeast strain that is heterozygous for about 55,000 SNPs, and employs SNP-Microarrays to map LOH events throughout the genome. These methods allow us to examine selected crossovers and unselected mitotic recombination events (crossover, noncrossover and BIR) at about 1 kb resolution across the genome. Using this method, we generated maps of spontaneous and UV-induced LOH events. In this study, we explore machine learning and variable selection techniques to build a predictive model for where the LOH events occur in the genome.
Randomly from the yeast genome, we simulated control tracts resembling the LOH tracts in terms of tract lengths and locations with respect to single-nucleotide-polymorphism positions. We then extracted roughly 1,100 features such as base compositions, histone modifications, presence of tandem repeats etc. and train classifiers to distinguish control tracts and LOH tracts. We found interesting features of good predictive values. We also found that with the current repertoire of features, the prediction is generally better for spontaneous LOH events than UV-induced LOH events.
Resumo:
BACKGROUND: Edoxaban, an oral direct factor Xa inhibitor, is in development for thromboprophylaxis, including prevention of stroke and systemic embolism in patients with atrial fibrillation (AF). P-glycoprotein (P-gp), an efflux transporter, modulates absorption and excretion of xenobiotics. Edoxaban is a P-gp substrate, and several cardiovascular (CV) drugs have the potential to inhibit P-gp and increase drug exposure. OBJECTIVE: To assess the potential pharmacokinetic interactions of edoxaban and 6 cardiovascular drugs used in the management of AF and known P-gp substrates/inhibitors. METHODS: Drug-drug interaction studies with edoxaban and CV drugs with known P-gp substrate/inhibitor potential were conducted in healthy subjects. In 4 crossover, 2-period, 2-treatment studies, subjects received edoxaban 60 mg alone and coadministered with quinidine 300 mg (n = 42), verapamil 240 mg (n = 34), atorvastatin 80 mg (n = 32), or dronedarone 400 mg (n = 34). Additionally, edoxaban 60 mg alone and coadministered with amiodarone 400 mg (n = 30) or digoxin 0.25 mg (n = 48) was evaluated in a single-sequence study and 2-cohort study, respectively. RESULTS: Edoxaban exposure measured as area under the curve increased for concomitant administration of edoxaban with quinidine (76.7 %), verapamil (52.7 %), amiodarone (39.8 %), and dronedarone (84.5 %), and exposure measured as 24-h concentrations for quinidine (11.8 %), verapamil (29.1 %), and dronedarone (157.6 %) also increased. Administration of edoxaban with amiodarone decreased the 24-h concentration for edoxaban by 25.7 %. Concomitant administration with digoxin or atorvastatin had minimal effects on edoxaban exposure. CONCLUSION: Coadministration of the P-gp inhibitors quinidine, verapamil, and dronedarone increased edoxaban exposure. Modest/minimal effects were observed for amiodarone, atorvastatin, and digoxin.