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The volumetric assessment and accurate grading of meningiomas before surgery are highly relevant for therapy planning and prognosis prediction. This study was to design a deep learning algorithm and evaluate the performance in detecting meningioma lesions and grade classification. In total, 5088 patients with histopathologically confirmed meningioma were retrospectively included. The pyramid scene parsing network (PSPNet) was trained to automatically detect and delineate the meningiomas. The results were compared to manual segmentations by evaluating the mean intersection over union (mIoU). The performance of grade classification was evaluated by accuracy. For the automated detection and segmentation of meningiomas, the mean pixel accuracy, tumor accuracy, background accuracy and mIoU were 99.68%, 81.36%, 99.88% and 81.36% for all patients; 99.52%, 84.86%, 99.93% and 84.86% for grade I meningiomas; 99.57%, 80.11%, 99.92% and 80.12% for grade II meningiomas; and 99.75%, 78.40%, 99.99% and 78.40% for grade III meningiomas, respectively. For grade classification, the accuracy values of the training and test datasets were 99.93% and 81.52% for all patients; 99.98% and 98.51% for grade I meningiomas; 99.91% and 66.67% for grade II meningiomas; and 99.88% and 73.91% for grade III meningiomas, respectively. The automated detection, segmentation and grade classification of meningiomas based on deep learning were accurate and reliable and may improve the monitoring and treatment of this frequently occurring tumor entity. Furthermore, the method could function as a useful tool for preassessment and preselection for radiologists, offering auxiliary information for clinical decision making in presurgical evaluation. [ABSTRACT FROM AUTHOR]

Although CRISPR-Cas9 nucleases are widely used for genome editing, the range of sequences that Cas9 can recognize is constrained by the need for a specific protospacer adjacent motif (PAM). As a result, it can often be difficult to target double-stranded breaks (DSBs) with the precision that is necessary for various genome-editing applications. The ability to engineer Cas9 derivatives with purposefully altered PAM specificities would address this limitation. Here we show that the commonly used Streptococcus pyogenes Cas9 (SpCas9) can be modified to recognize alternative PAM sequences using structural information, bacterial selection-based directed evolution, and combinatorial design. These altered PAM specificity variants enable robust editing of endogenous gene sites in zebrafish and human cells not currently targetable by wild-type SpCas9, and their genome-wide specificities are comparable to wild-type SpCas9 as judged by GUIDE-seq analysis. In addition, we identify and characterize another SpCas9 variant that exhibits improved specificity in human cells, possessing better discrimination against off-target sites with non-canonical NAG and NGA PAMs and/or mismatched spacers. We also find that two smaller-size Cas9 orthologues, Streptococcus thermophilus Cas9 (St1Cas9) and Staphylococcus aureus Cas9 (SaCas9), function efficiently in the bacterial selection systems and in human cells, suggesting that our engineering strategies could be extended to Cas9s from other species. Our findings provide broadly useful SpCas9 variants and, more importantly, establish the feasibility of engineering a wide range of Cas9s with altered and improved PAM specificities. [ABSTRACT FROM AUTHOR]

With the continuous development of gold ore prospecting and exploration in recent years a new type of micro-disseminated gold deposits have been found in the regions of Southwest Guizhou Province and Northwest Guangxi Zhuang Autonomous Region, with the orebodies directly occurring in diabase or in the contact zone between diabase and strata. The orebodies are strictly controlled by fault structures. The discovery of this type of gold deposits has brought about new prospects for gold ore prospecting in the Yunnan-Guizhou-Guangxi Golden Triangle region. From the preliminary analysis of the geological characteristics of the Qiaoxiang gold deposit in Wangmo County, in combination with the results of research work in the adjacent areas in recent years, this paper roughly described the geological characteristics and metallogenic conditions of this type of gold ore deposits with an attempt to make more and more geologists pay enough attention to this type of gold ore deposits, so as to promote gold ore prospecting in Guizhou Province to develop toward a variety of types of gold deposits in all round way. [ABSTRACT FROM AUTHOR]