Background The polymorphisms of VKORC1 and CYP2C9 play increasingly important roles in the inter-individual variability in warfarin dose. This study aimed to evaluate the feasibility of clinical application of pharmacogenetic-based warfarin-dosing algorithm in patients of Han nationality with rheumatic heart disease after valve replacement in a randomized and controlled trial. Methods One hundred and one consecutive patients of Han nationality with rheumatic heart disease undergoing valve surgery were enrolled and randomly assigned to an experimental group (n=50, based on CYP2C9 and VKORC1 genotypes, pharmacogenetic-based “predicted warfarin dose” for 3 days and then was adjusted to INR until stable warfarin maintenance dose) or a control group (n=51, 2.5mg/d for 3 days and then was adjusted to INR until stable warfarin maintenance dose). All included patients were followed for 50 days after initiation of warfarin therapy. The primary end-point was the time to reach a stable warfarin maintenance dose. Results During the follow-up, 84.0% patients in the experimental group and 58.8% patients in the control group received warfarin maintenance dose. Compared with control group, patients in the experimental group had shorter mean time elapse from initiation of warfarin therapy until warfarin maintenance dose (27.5±1.8 d versus 34.7±1.8 d, p<0.001). Cox regression revealed that group (HR for experimental versus control group: 1.568, 95%CI 1.103-3.284) and age were two significant variables related to the time elapse from initiation of warfarin therapy until warfarin maintenance dose. The predicted warfarin maintenance dose was prominently correlated with the actual warfarin maintenance dose (r=0.684, p<0.001). Conclusion: Based on CYP2C9 and VKORC1 genotypes, the pharmacogenetic-based warfarin-dosing algorithm may shorten the time elapse from initiation of warfarin therapy until warfarin maintenance dose. It is feasible for the clinical application of the pharmacogenetic-based warfarin-dosing algorithm in patients of Han nationality with rheumatic heart disease after valve replacement.
We studied the evolution of cooperation in the prisoner's dilemma game on a square lattice where the size of the interaction neighborhood is considered. Firstly, the effects of noise and the cost-to-benefit ratio on the maintenance of cooperation were investigated. The results indicate that the cooperation frequency depends on the noise and cost-to-benefit ratio: cooperation reaches a climax as noise increases, but it monotonously decreases and even vanishes with the ratio increasing. Furthermore, we investigated how the size of the interaction neighborhood affects the emergence of cooperation in detail. Our study demonstrates that cooperation is remarkably enhanced by an increase in the size of the interaction neighborhood. However, cooperation died out when the size of the interaction neighborhood became too large since the system was similar to the mean-field system. On this basis, a cluster-forming mechanism acting among cooperators was also explored, and it showed that the moderate range of the neighborhood size is beneficial for forming larger cooperative clusters. Finally, large-scale Monte Carlo simulations were carried out to visualize and interpret these phenomena explicitly. [11][12][13][14][15][16]. As a paradigm of pair-wise interaction games, the prisoner's dilemma game (PDG) has attracted much attention [17][18][19][20][21]. In the original form of the PDG, there are two behavior options: each of two players must simultaneously choose to cooperate (C) or to defect (D). If both players choose C, they will receive the reward R separately, but only the punishment P for mutual defection. If two players take different strategies, then the defector will get the highest payoff of temptation T, while the cooperator will be left with the lowest sucker's payoff S. These payoffs usually satisfy the elementary payoff ranking T > R > P > S and the additional required condition (T + S) < 2R in repeated interactions. Henceforth, defection is the optimal choice for each player irrespective of the decision of his opponent, and defection will become widespread. Every player will end up with the payoff P instead of the payoff R, which yields the social dilemmas as depicted in [22]. According to the motivation of the non-equilibrium kinetic Ising model in statistical physics, the PDG has been well studied for a spatially structured population in past decades [11][12][13][14][15][16][17][18][19][20][21][22][23]. In these models, players are distributed at the sites of different lattices or graphs, and each player can update his/her strategy and has a given probability of adopting his/her neighbor's strategies at each time step. Recently, many real systems have been found to exhibit
The clonal diversity of Clintonia udensis Trautv. et Mey. was detected by ISSR markers among 16 populations, and its correlation with ecological factors was analyzed as well in this work. Results showed that individuals (clonal ramets) per genotype were 1.12 and 1.149 at population and species levels, respectively, and that the 16 populations were all multiclonal. The detected genotypes were localized, without exception, within populations but demonstrated relatively high clonal differentiation among populations. The clonal diversity of the studied populations was high, with the average Simpson's index of 0.975, while the genets showed a clonal architecture of "guerilla". The population genetic diversities revealed by genet were consistent with those by ramet, further confirming their genetic differentiation among populations. And its genotype diversity within populations probably resulted largely from the frequent seedling regeneration and self-compatibility. In addition, the correlation analysis further revealed that, among the ecological factors, Simpson's index of C. udensis had a significant positive correlation (P<0.05) with pH values in the soil but not others.
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