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Kinase alterations are increasingly recognised as oncogenic drivers in mesenchymal tumours. Infantile fibrosarcoma and the related renal tumour, congenital mesoblastic nephroma, were among the first solid tumours shown to harbour recurrent tyrosine kinase fusions, with the canonical ETV6::NTRK3 fusion identified more than 20 years ago. Although targeted testing has long been used in diagnosis, the advent of more robust sequencing techniques has driven the discovery of kinase alterations in an array of mesenchymal tumours. As our ability to identify these genetic alterations has improved, as has our recognition and understanding of the tumours that harbour these alterations. Specifically, this study will focus upon mesenchymal tumours harbouring NTRK or other kinase alterations, including tumours with an infantile fibrosarcoma-like appearance, spindle cell tumours resembling lipofibromatosis or peripheral nerve sheath tumours and those occurring in adults with a fibrosarcoma-like appearance. As publications describing the histology of these tumours increase so, too, do the variety kinase alterations reported, now including NTRK1/2/3, RET, MET, RAF1, BRAF, ALK, EGFR and ABL1 fusions or alterations. To date, these tumours appear locally aggressive and rarely metastatic, without a clear link between traditional features used in histological grading (e.g. mitotic activity, necrosis) and outcome. However, most of these tumours are amenable to new targeted therapies, making their recognition of both diagnostic and therapeutic import. The goal of this study is to review the clinicopathological features of tumours with NTRK and other tyrosine kinase alterations, discuss the most common differential diagnoses and provide recommendations for molecular confirmation with associated treatment implications.  相似文献   
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ObjectiveEach pulmonary segment is an anatomical and functional unit. However, it is fundamentally difficult to precisely distinguish every pulmonary segment using the conventional pulmonary intersegmental planes from computed tomography images. Building arteriopulmonary segments is likely to be an effective way to identify pulmonary segments.MethodsThe thoracic computed tomography images of 40 patients were collected. The anatomic structures of interest were extracted in the transverse, sagittal, and coronal planes using the semi-automated segmentation tools provided by Amira software. The intrapulmonary vessels were subsequently segmented and reconstructed. The distributions of the pulmonary arteries, veins, and bronchi were observed. In patients with pulmonary masses, the mass was also reconstructed.ResultsThe three-dimensional reconstructed images showed the branches of the pulmonary artery ramified up to their eighth order covering the entire lung as well as evident intersegmental gaps without pulmonary arteries. The segmental artery was closely accompanied by the segmental bronchi in 486 pulmonary segments (90% of total number of segments). The size and spatial location of the pulmonary mass within a pulmonary segment were also clearly visible.ConclusionsDemarcation of arteriopulmonary segments can be used to precisely distinguish every pulmonary segment and provide its detailed anatomical structure before pulmonary segmentectomy.  相似文献   
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“三全育人”是高校思政教育工作的关键一环,也是中医药高校推动思政教育的重要内容。以“三全育人”为视角对北京中医药大学思想政治教育举措“杏林成长导师”计划路径、内容深入分析,运用统计分析和文献研究方法,剖析该计划对中医学专业大学生的学业、思想和实践等多个层面的现实成效,从而为“三全育人”理念在中医药院校制度建构中的应用提供新的视角与方法。  相似文献   
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Gestational trophoblastic neoplasia (GTN) patients are treated according to the eight-variable International Federation of Gynaecology and Obstetrics (FIGO) scoring system, that aims to predict first-line single-agent chemotherapy resistance. FIGO is imperfect with one-third of low-risk patients developing disease resistance to first-line single-agent chemotherapy. We aimed to generate simplified models that improve upon FIGO. Logistic regression (LR) and multilayer perceptron (MLP) modelling (n = 4191) generated six models (M1-6). M1, all eight FIGO variables (scored data); M2, all eight FIGO variables (scored and raw data); M3, nonimaging variables (scored data); M4, nonimaging variables (scored and raw data); M5, imaging variables (scored data); and M6, pretreatment hCG (raw data) + imaging variables (scored data). Performance was compared to FIGO using true and false positive rates, positive and negative predictive values, diagnostic odds ratio, receiver operating characteristic (ROC) curves, Bland-Altman calibration plots, decision curve analysis and contingency tables. M1-6 were calibrated and outperformed FIGO on true positive rate and positive predictive value. Using LR and MLP, M1, M2 and M4 generated small improvements to the ROC curve and decision curve analysis. M3, M5 and M6 matched FIGO or performed less well. Compared to FIGO, most (excluding LR M4 and MLP M5) had significant discordance in patient classification (McNemar's test P < .05); 55-112 undertreated, 46-206 overtreated. Statistical modelling yielded only small gains over FIGO performance, arising through recategorisation of treatment-resistant patients, with a significant proportion of under/overtreatment as the available data have been used a priori to allocate primary chemotherapy. Streamlining FIGO should now be the focus.  相似文献   
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Journal of Immigrant and Minority Health - COVID-19 has disproportionally affected underrepresented minorities (URM) and low-income immigrants in the United States. The aim of the study is to...  相似文献   
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