Shorter grain-filling period and rapid endosperm development endow weedy rice (WR) with early maturity compared to cultivated rice (CR). However, the role of the cytological features and antioxidative enzyme system during grain development are largely unexplored. We selected four biotypes of WR and their associated cultivated rice (ACR) types from different latitudes to conduct a common garden experiment. The difference in the cytological features of endosperm between WR and ACR was compared by chemical staining, and the cell viability and nuclear morphometry of endosperm cells were observed by optical microscopy. Furthermore, antioxidative enzyme activity was measured during grain filling. Anatomic observation of endosperm shows that the development process of endosperm cell in WR was more rapid and earlier than that in ACR. The percentage of degraded nuclei of WR was 2–83% more than that of ACR. Endosperm cells in WR lost viability 2–6 days earlier than those in ACR. The antioxidant enzyme activity of WR was lower than that of ACR during grain filling. The ability of WR to scavenge reactive oxygen species (ROS) was weaker than that of ACR, which may contribute to the rapid cytological process in the endosperm cells of WR. The rapid cytological process and weaker ability to scavenge ROS in endosperm cells may contribute to early maturity in WR.
Angeletti Cesar,Harvey Neal R,Khomitch Vitali,Fischer Andrew H,Levenson Richard M,Rimm David L
Despite low sensitivity (around 60%), cytomorphologic examination of urine specimens represents the standard procedure in the diagnosis and follow-up of bladder cancer. Although color is information-rich, morphologic diagnoses are rendered almost exclusively on the basis of spatial information. We hypothesized that quantitative assessment of color (more precisely, of spectral properties) using liquid crystal-based spectral fractionation, combined with genetic algorithm-based spatial analysis, can improve the accuracy of traditional cytologic examination. Images of various cytological specimens were collected every 10?nm from 400 to 700?nm to create an image stack. The resulting data sets were analyzed using the Los Alamos-developed GENetic Imagery Exploitation (GENIE) package, a hybrid genetic algorithm that segments (classifies) images using automatically ‘learned’ spatio-spectral features. In an evolutionary fashion, GENIE generates a series of algorithms or ‘chromosomes’, keeping the one with best fitness with respect to a user-defined training set. First, we tested the system to determine if it could recognize malignant cells using artificial cytology specimens constructed to completely avoid the requirement for human interpretation. GENIE was able to differentiate malignant from benign cells and to estimate their relative proportions in controlled mixtures. We then tested the system on routine cytology specimens. When targeted to detect malignant urothelial cells in cytology specimens, GENIE showed a combined sensitivity and specificity of 85 and 95%, in samples drawn from two separate institutions over a span of 4 years. When trained on cases initially diagnosed as ‘atypical’ but with unequivocal follow-up by biopsy, surgical specimen or cytology, GENIE showed efficiency superior to the cytopathologist with respect to predicting the follow-up result in a cohort of 85 cases. We believe that, in future, this type of methodology could be used as an ancillary test in cytopathology, in a manner analogous to immunostaining, in those situations when a definitive diagnosis cannot be rendered based solely on the morphology.
危险品化学品经营许可证（带存储）