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21.
We used scanning electron microscopy (SEM) and transmission electron microscopy (TEM) to observe the oral organelle, cytopharynx, and subpellicular structure of a Dileptus sp. The main results were as follows: (a) the cytostome was located on the ventral surface of the base of the beak, surrounded by a periportal matrix that integrated 135 microtube bundles. When these microtube bundles contract, radially arranged into a disk, the cytostome was closed. When these microtube bundles were stretch, they fell into the cytostome and opens. The diameter of the cytostome was about 16 μm regardless of its closure or opening, indicating that the contraction or elongation of these microtube bundles did not change the size of the cytostome, which was only related to whether it blocked the cytostome, thus determining the opening and closing of the cytostome. There were many microtube bundles on two sides of the feeding trough, which could widen or narrow the feeding trough and facilitate beak feeding. (b) The cytopharynx was basket‐like without a bottom with a diameter of about 6 μm and was woven from two kind fibers about 0.08 and 0.19 μm. (c) There were two types of extrusomes under the pellicle. Using transmission electron microscopy,the Type I extrusomes showed narrow and long egg shape, its cross section was circular which is composed by various electronic density of concentric. Using the scanning electron microscope, they were two slightly thin clavate, the length was about 5 μm, the diameter of the middle section was about 0.75 μm, and the diameter of the two ends was about 0.32 μm, they were distributed abundantly between the microtubule fasciculi which were located on both sides of the gap on the feeding groove. Using transmission electron microscopy, the Type II extrusomes showed egg shape. Using the scanning electron microscopy, they were about 1.6 × 0.8 μm in size, they were distributed abundantly under the body pellicle while rarely the proboscis. In addition, many different of developmental stages two types of extrusomes could be also seen in the cytoplasm. (d) There were very well‐developed fibrous systems under the pellicle that were woven from fibers about 0.14 μm in diameter that attached to the pellicle and bound some organelles in the cytoplasm (e.g., mitochondria, extrusomes) and other structures to the cytoplasm and maintained cell morphology. The results of this study not only supplement and enrich the morphological contents of the Dileptus sp., but also provide the basis for the study of the taxonomy of the Dileptus sp. It also provides a new method for researchers to explore the morphology and structure of ciliate cells under the cortex by SEM. 相似文献
22.
AbstractBreast cancer is a common malignancy with poor prognosis. Cancer cells are heterogeneous and cancer stem cells (CSCs) are primarily responsible for tumor relapse, treatment-resistance and metastasis, so for breast cancer stem cells (BCSCs). Diets are known to be associated with carcinogenesis. Food-derived polyphenols are able to attenuate the formation and virulence of BCSCs, implying that these compounds and their analogs might be promising agents for preventing breast cancer. In the present review, we summarized the origin and surface markers of BCSCs and possible mechanisms responsible for the inhibitory effects of polyphenols on BCSCs. The suppressive effects of common dietary polyphenols against BCSCs, such as curcumin, epigallocatechin gallate (EGCG) and related polyphenolic compounds were further discussed. 相似文献
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Traditionally, in supervised machine learning, (a significant) part of the available data (usually 50%-80%) is used for training and the rest—for validation. In many problems, however, the data are highly imbalanced in regard to different classes or does not have good coverage of the feasible data space which, in turn, creates problems in validation and usage phase. In this paper, we propose a technique for synthesizing feasible and likely data to help balance the classes as well as to boost the performance in terms of confusion matrix as well as overall. The idea, in a nutshell, is to synthesize data samples in close vicinity to the actual data samples specifically for the less represented (minority) classes. This has also implications to the so-called fairness of machine learning. In this paper, we propose a specific method for synthesizing data in a way to balance the classes and boost the performance, especially of the minority classes. It is generic and can be applied to different base algorithms, for example, support vector machines, k-nearest neighbour classifiers deep neural, rule-based classifiers, decision trees, and so forth. The results demonstrated that (a) a significantly more balanced (and fair) classification results can be achieved and (b) that the overall performance as well as the performance per class measured by confusion matrix can be boosted. In addition, this approach can be very valuable for the cases when the number of actual available labelled data is small which itself is one of the problems of the contemporary machine learning. 相似文献
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