Background The purpose of this study was to investigate an association between EGFR mutation status and 18 F‐fluorodeoxyglucose positron emission tomography‐computed tomography ( 18 F‐FDG PET‐CT) image features in lung adenocarcinoma. Methods Retrospective analysis of the data of 139 patients with lung adenocarcinoma confirmed by surgical pathology who underwent preoperative 18 F‐FDG PET‐CT was conducted. Correlations between EGFR mutation status, clinical characteristics, and PET‐CT parameters, including the maximum standardized uptake value (SUVmax), the mean of the SUV (SUVmean), the peak of the SUV (SUVpeak) of the primary tumor, and the ratio of SUVmax between the primary tumor and the mediastinal blood pool (SUVratio), were statistically analyzed. Multivariate logistic regression analysis was performed to identify predictors of EGFR mutation. Receiver operating characteristic curves of statistical quantitative parameters were compared. Results EGFR mutations were detected in 74 (53.2%) of the 139 lung adenocarcinomas and were more frequent in non‐smoking patients. Univariate analysis showed that the SUVmax, SUVmean, SUVpeak, and SUVratio were lower in EGFR ‐mutated than in wild‐type tumors. The receiver operating characteristic curves showed no significant differences between their diagnostic efficiencies. Multivariate logistic regression analysis showed that being a never smoker was an independent predictor of EGFR mutation. Conclusion Quantitative parameters based on 18 F‐FDG PET‐CT have modest power to predict the presence of EGFR mutation in lung adenocarcinoma; however, when compared to smoking history, they are not good or significant predictive factors.

We hybridized 10 chromosome segment substitution lines (CSSLs) each from two CSSL populations and produced 50 F1 hybrids according to North Carolina Design II. We analyzed the genetic effects and heterosis of yield and yield components in the F1 hybrids and parents in four environments via the additive-dominance genetic model. Yield and yield components of the CSSLs were controlled by combined additive and dominance effects, and lint percentage was mainly controlled by additive effects, but boll weight, boll number, seedcotton yield and lint yield were mainly controlled by dominance effects. We detected significant interaction effects between genetics and the environment for all yields traits. Similar interactions were detected between two CSSL populations (Pop CCRI 36 and Pop CCRI 45). Significant positive mid-parent heterosis was detected for all yield traits in both populations, and significant positive better-parent heterosis was also detected for all yield traits except lint percentage. The differences among parents were relatively small, but significant heterosis was detected for yield and yield components. Therefore, the relationship between heterosis and genetic distance for yield traits is complicated and requires further study. These CSSLs represent useful tools for improving yield and yield components in cotton.

Photostimulable luminescence (PSL) nanophosphors, which exhibit superior features including controllable energy storage and efficient photon release upon light stimulation, are desirable for optical signal storage. However, trap tuning of the storage phosphor remains a great challenge. Herein, the PSL of Zn2GeO4:Mn2+ nanophosphors is enhanced via creating deep traps through nonequivalent Pr3+ doping. The possible enhanced mechanisms are analyzed combined with doping models using the first-principles theory. A mechanism is proposed based on changing the coordination environment of Mn2+, creating deep traps and tuning the band gap structure, and thus providing the chance for electrons’ photoionization and PSL generation. As a result, the prepared nanophosphors demonstrate the superior functionalities for optical signal storage. This work not only offers an insight into defect engineering through doping strategies for developing PSL materials but also supplies a good candidate for optical information storage.

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