Effect of Implant vs. Tissue Reconstruction on Cancer Specific Survival Varies by Axillary Lymph Node Status in Breast Cancer Patients

BackgroundTo compare the breast cancer-specific survival (BCSS) between patients who underwent tissue or implant reconstruction after mastectomy.MethodWe used the database from Surveillance, Epidemiology, and End Results (SEER) registries and compared the BCSS between patients who underwent tissue and implant reconstruction after mastectomy. Cox-regression models were fitted, adjusting for known clinicopathological features. The interaction between the reconstruction types (tissue/implant) and nodal status (N-stage) was investigated.ResultsA total of 6,426 patients with a median age of 50 years were included. With a median follow up of 100 months, the 10-year cumulative BCSS and non-BCSS were 85.1% and 95.4%, respectively. Patients who underwent tissue reconstruction had tumors with a higher T-stage, N-stage, and tumor grade and tended to be ER/PR-negative compared to those who received implant reconstruction. In univariate analysis, implant-reconstruction was associated with a 2.4% increase (P = 0.003) in the BCSS compared with tissue-reconstruction. After adjusting for significant risk factors of the BCSS (suggested by univariate analysis) and stratifying based on the N-stage, there was only an association between the reconstruction type and the BCSS for the N2-3 patients (10-year BCSS of implant vs. tissue-reconstruction: 68.7% and 59.0%, P = 0.004). The 10-year BCSS rates of implant vs. tissue-reconstruction were 91.7% and 91.8% in N0 patients (P>0.05) and 84.5% and 84.4% in N1 patients (P>0.05), respectively.ConclusionsThe implant (vs. tissue) reconstruction after mastectomy was associated with an improved BCSS in N2-3 breast cancer patients but not in N0-1 patients. A well-designed, prospective study is needed to further confirm these findings.     

Systematically Constructing Kinetic Transition Network in Polypeptide from Top to Down: Trajectory Mapping

Molecular dynamics (MD) simulation is an important tool for understanding bio-molecules in microscopic temporal/spatial scales. Besides the demand in improving simulation techniques to approach experimental scales, it becomes more and more crucial to develop robust methodology for precisely and objectively interpreting massive MD simulation data. In our previous work [J Phys Chem B 114, 10266 (2010)], the trajectory mapping (TM) method was presented to analyze simulation trajectories then to construct a kinetic transition network of metastable states. In this work, we further present a top-down implementation of TM to systematically detect complicate features of conformational space. We first look at longer MD trajectory pieces to get a coarse picture of transition network at larger time scale, and then we gradually cut the trajectory pieces in shorter for more details. A robust clustering algorithm is designed to more effectively identify the metastable states and transition events. We applied this TM method to detect the hierarchical structure in the conformational space of alanine-dodeca-peptide from microsecond to nanosecond time scales. The results show a downhill folding process of the peptide through multiple pathways. Even in this simple system, we found that single common-used order parameter is not sufficient either in distinguishing the metastable states or predicting the transition kinetics among these states.     

急性髓系白血病相关基因的DNA甲基化

急性髓系白血病(acute myeloid leukemia,AML)是异质性造血干细胞恶性克隆性疾病,主要表现为外周血、骨髓以及其他组织中的原始细胞克隆性扩增。近年来,AML发病率呈逐年增加的趋势,对人类健康产生巨大的威胁。在不同种族及不同性别中,AML发病率及死亡率存在显著差异。AML是一种复杂疾病,与遗传突变及异常表观遗传修饰密切相关。DNA甲基化是重要的表观遗传修饰,AML相关基因的异常DNA甲基化修饰对疾病的发生发展极其重要。该文对AML相关基因的异常甲基化修饰进行了系统的作用机制分析,并对重要基因进行了功能分类。该文总结的具有异常DNA甲基化修饰的基因,有望辅助预测AML的治疗及预后效果,并为设计个体化AML治疗方案提供全新的思路。     

Stressful colours: corticosterone concentrations in a free-living songbird vary with the spectral composition of experimental illumination

Organisms have evolved under natural daily light/dark cycles for millions of years. These cycles have been disturbed as night-time darkness is increasingly replaced by artificial illumination. Investigating the physiological consequences of free-living organisms in artificially lit environments is crucial to determine whether nocturnal lighting disrupts circadian rhythms, changes behaviour, reduces fitness and ultimately affects population numbers. We make use of a unique, large-scale network of replicated field sites which were experimentally illuminated at night using lampposts emanating either red, green, white or no light to test effect on stress hormone concentrations (corticosterone) in a songbird, the great tit (Parus major). Adults nesting in white-light transects had higher corticosterone concentrations than in the other treatments. We also found a significant interaction between distance to the closest lamppost and treatment type: individuals in red light had higher corticosterone levels when they nested closer to the lamppost than individuals nesting farther away, a decline not observed in the green or dark treatment. Individuals with high corticosterone levels had fewer fledglings, irrespective of treatment. These results show that artificial light can induce changes in individual hormonal phenotype. As these effects vary considerably with light spectrum, it opens the possibility to mitigate these effects by selecting street lighting of specific spectra.     

Evaluation of Methyl Bromide Alternatives Efficacy against Soil-Borne Pathogens,Nematodes and Soil Microbial Community

Methyl bromide (MB) and other alternatives were evaluated for suppression of Fusarium spp., Phytophthora spp., and Meloidogyne spp. and their influence on soil microbial communities. Both Fusarium spp. and Phytophthora spp. were significantly reduced by the MB (30.74 mg kg^-1), methyl iodide (MI: 45.58 mg kg^-1), metham sodium (MS: 53.92 mg kg^-1) treatments. MS exhibited comparable effectiveness to MB in controlling Meloidogyne spp. and total nematodes, followed by MI at the tested rate. By contrast, sulfuryl fluoride (SF: 33.04 mg kg^-1) and chloroform (CF: 23.68 mg kg^-1) showed low efficacy in controlling Fusarium spp., Phytophthora spp., and Meloidogyne spp. MB, MI and MS significantly lowered the abundance of different microbial populations and microbial biomass in soil, whereas SF and CF had limited influence on them compared with the control. Diversity indices in Biolog studies decreased in response to fumigation, but no significant difference was found among treatments in PLFA studies. Principal component and cluster analyses of Biolog and PLFA data sets revealed that MB and MI treatments greatly influenced the soil microbial community functional and structural diversity compared with SF treatment. These results suggest that fumigants with high effectiveness in suppressing soil-borne disease could significantly influence soil microbial community.     

Studies of Antibiotic Resistance of Beta-Lactamase Bacteria under Different Nutrition Limitations at the Single-Cell Level

Drug resistance involves many biological processes, including cell growth, cell communication, and cell cooperation. In the last few decades, bacterial drug resistance studies have made substantial progress. However, a major limitation of the traditional resistance study still exists: most of the studies have concentrated on the average behavior of enormous amounts of cells rather than surveying single cells with different phenotypes or genotypes. Here, we report our study of beta-lactamase bacterial drug resistance in a well-designed microfluidic device, which allows us to conduct more controllable experiments, such as controlling the nutrient concentration, switching the culture media, performing parallel experiments, observing single cells, and acquiring time-lapse images. By using GFP as a beta-lactamase indicator and acquiring time-lapse images at the single-cell level, we observed correlations between the bacterial heterogeneous phenotypes and their behavior in different culture media. The feedback loop between the growth rate and the beta-lactamase production suggests that the beta-lactamase bacteria are more resistant in a rich medium than in a relatively poor medium. In the poorest medium, the proportion of dormant cells may increase, which causes a lower death rate in the same generation. Our work may contribute to assaying the antibiotic resistance of pathogenic bacteria in heterogeneous complex media.     

Intrinsic Multi-Scale Dynamic Behaviors of Complex Financial Systems

The empirical mode decomposition is applied to analyze the intrinsic multi-scale dynamic behaviors of complex financial systems. In this approach, the time series of the price returns of each stock is decomposed into a small number of intrinsic mode functions, which represent the price motion from high frequency to low frequency. These intrinsic mode functions are then grouped into three modes, i.e., the fast mode, medium mode and slow mode. The probability distribution of returns and auto-correlation of volatilities for the fast and medium modes exhibit similar behaviors as those of the full time series, i.e., these characteristics are rather robust in multi time scale. However, the cross-correlation between individual stocks and the return-volatility correlation are time scale dependent. The structure of business sectors is mainly governed by the fast mode when returns are sampled at a couple of days, while by the medium mode when returns are sampled at dozens of days. More importantly, the leverage and anti-leverage effects are dominated by the medium mode.