A Priori Subcell Limiting Approach for the FR/CPR Method on Unstructured Meshes

A priori subcell limiting approach is developed for high-order flux reconstruction/correction procedure via reconstruction (FR/CPR) methods on two-dimensional unstructured quadrilateral meshes. Firstly, a modified indicator based on modal energy coefficients is proposed to detect troubled cells, where discontinuities exist. Then, troubled cells are decomposed into nonuniform subcells and each subcell has one solution point. A second-order finite difference shock-capturing scheme based on nonuniform nonlinear weighted (NNW) interpolation is constructed to perform the calculation on troubled cells while smooth cells are calculated by the CPR method. Numerical investigations show that the proposed subcell limiting strategy on unstructured quadrilateral meshes is robust in shock-capturing.     

菊花总黄酮含药血清对干眼细胞模型AR、NF-κB磷酸化蛋白及TGF-β1表达的影响＊

目的 观察菊花总黄酮在体外条件下对泪腺上皮细胞中雄激素受体（Androgen Receptor，AR）的调控作用及对下游的核因子κB（Nuclear Factor kappa B，NF-κB）、转化生长因子-β1（transforming growth factor-beta1，TGF-β1）的表达影响。方法 以过氧化氢（H₂O₂）诱导泪腺上皮细胞凋亡，建立细胞模型，设立无雄激素培养空白对照组、含雄激素培养对照组、无雄激素培养黄酮治疗组。以MTT法摸索含药血清最佳干预加入量；免疫印迹实验（Western Blot）以及实时荧光定量PCR法（Quantitative Real-Time PCR，qPCR）检测泪腺上皮细胞中AR、NF-κB及TGF-β1的表达情况；并应用雄激素受体阻断剂氟他胺进行AR阻断后再次检测上述指标 。结果 MTT法检测后计算得出含药血清干预细胞的最终浓度为13.2%；无雄激素培养黄酮治疗组及含雄激素培养对照组中AR、NF-κB及TGF-β1的表达增强，与空白对照组对比有显著差异（P<0.01）；无雄激素培养黄酮治疗组中NF-κB表达量比含雄激素培养对照组表达量低，两者间的差异有统计学意义。氟他胺及含药血清干预后，无雄激素培养黄酮治疗组及含雄激素培养对照组中AR及NF-κB的表达未见提高，无统计学意义。结论 菊花总黄酮对泪腺上皮细胞可能存在拟雄激素效应，从而使AR、NF-κB表达增加，并通过上调TGF-β1的表达，可能起到在泪腺局部的抗炎作用。     

Risk as a pattern over time: Delineation of time-dependent risk factors in biological,psychological, and social variables in cancer patients

Background

Survival in cancer patients is associated with a multitude of biological, social, and psychological factors. Although it is well established that all these factors add to overall mortality, it is not well understood how the predictive power of these parameters changes in a comprehensive model and over time.

Methods

Patients who attended the authors’ outpatient clinic were invited to participate. The authors followed 5180 mixed cancer patients (51.1% female; mean age, 59.1 years [SD = 13.8]) for up to 16 years and analyzed biological (age, sex, cancer site, anemia), psychological (anxiety, depression), and social variables (marital status, education, employment status) potentially predicting overall survival in a Cox proportional hazards model.

Results

The median survival time for the entire sample was 4.3 years (95% confidence interval, 4.0–4.7). The overall survival probabilities for 1 and 10 years were 76.8% and 38.0%, respectively. Following an empirical approach, the authors split the time interval into five periods: acute, subacute, short-term, medium-term, and long-term. A complex pattern of variables predicted overall survival differently in the five periods. Biological parameters were important throughout most of the time, social parameters were either time-independent predictors or tended to be more important in the longer term. Of the psychological parameters, only depression was a significant predictor and lost its predictive power in the long-term.

Conclusions

The findings of this study allow the development of comprehensive patient-specific models of risk and resilience factors addressing biopsychosocial needs of cancer patients, paving the way for a personalized treatment plan that goes beyond biomedical cancer care.