Controlling the regioregularity among the structural units of narrow bandgap conjugated polymer backbones has led to improvements in optoelectronic properties, for example in the mobilities observed in field effect transistor devices. To investigate how the regioregularity affects quantities relevant to hole transport, regioregular and regiorandom oligomers representative of polymeric structures were studied using density functional theory. Several structural and electronic characteristics of the oligomers were compared, including chain planarity, cation spin density, excess charges on molecular units and internal reorganizational energy. The main difference between the regioregular and regiorandom oligomers is found to be the conjugated backbone planarity, while the reorganizational energies calculated are quite similar across the molecular family. This work constitutes the first step on understanding the complex interplay of atomistic changes and an oligomer backbone structure toward modeling the charge transport properties.

In order to analyze biogenic volatile organic compounds in the atmosphere, an automated gas chromatography is developed and employed at the laboratory of National Center for Atmospheric Research (NCAR) during January to July, 2000. A small refrigerator was used so as to remove water in the air sample from gas line, and get accurate concentrations of volatile organic compounds. At 5°C, good water removing efficiency can be obtained at controlled flow rate. Air samples were collected around the building of Mesa Lab. of NCAR and analyzed by this gas chromatography system. This paper reports this gas chromatography system and results of air samples. The experimental results show that this gas chromatography system has a good reproducibility and stability, and main interesting volatile organic compounds such as isoprene, monoterpenes have an evident diurnal variation.

While it is well known that there are interspecies differences in Ag sensitivity, differences in the cytotoxic responses of mammalian cells to silver nanoparticles (Ag NPs) are also observed. In order to explore these response outcomes, six cell lines, including epithelial cells (Caco-2, NHBE, RLE-6TN, and BEAS-2B) and macrophages (RAW 264.7 and THP-1) of human and rodent origin, are exposed to 20 nm citrate- and PVP-coated Ag NPs with Au cores, as well as 20 nm citrate-coated particles without cores. An MTS assay shows that while Caco-2 and NHBE cells are resistant to particles over a 0.1-50 μg mL^-1 dose range, RAW 264.7, THP-1, RLE-6TN, and BEAS-2B cells are more susceptible. While there are small differences in dissolution rates, there are no major differences in the cytotoxic potential of the different particles. However, differences in anti-oxidant defense and metallothionein expression among different cell types are observed, which can partially explain differential Ag NP sensitivity. So, it is important to consider these differences in understanding the potential heterogeneous effects of nano Ag on mammalian biological systems. Different mammalian cell lines show different sensitivities to silver nanoparticles due partly to the efficient activation of antioxidant defense and metallothionein expression in resistant cell lines compared to susceptible cell lines.

Purpose/objective(s)

In oncology, retrospective cohort studies are often used for comparative effectiveness research, studies that compare the efficacy of treatment A vs B. We examine the stability of these estimates using biostatistical methods for bias correction with varying sets of covariates. We hypothesize that retrospective comparative effectiveness research studies are sensitive to biostatistical analytic choices; by varying the methods, there will be significant instability and lack of consistency in conclusions.

Materials/methods

We evaluated three disease sites in oncology where the addition of local therapy over systemic therapy alone has been hypothesized to improve survival in the metastatic setting: lung, prostate, and female breast, using multivariable Cox regression analyses. Patient data were extracted from the National Cancer Database, 2004-2014. We employed various statistical techniques to adjust for selection bias and immortal time bias, including propensity score matching, left truncation adjustment, and landmark analysis. Further, we used combinations of covariates in regression models to generate hazard ratios (HRs) with 95% confidence intervals. We constructed plots of -log10(P-value) vs HR to quantify the variability of estimates.

Results

There were 72,549 lung, 14,904 prostate, and 13,857 female breast cancer patients included. We ran > 300,000 regression models, where each model represents a publishable study. Without propensity score matching or immortal time bias adjustment, all multivariable models provided HRs that favored the addition of local therapy for all cancers, with HRs < 1, and all P-values < 0.001. Once propensity score matching was added to our analysis, higher HRs were observed, but most were still < 1. When landmark analysis and covariate combinations were used, we generated HRs that were < 1, equal to 1, and > 1, with 100-fold differences in -log10(P-values).

Conclusion

By altering the biostatistical approach with varying combinations of covariates, we were able to generate contrary outcomes and statistical significance. Our results suggest that some retrospective observational studies may find a treatment helps, and another may find it does not, simply based on analytic choices. This paradox highlights the importance of randomized controlled trials, and may explain the discordance noted in prior studies comparing observational trials and randomized studies.