Mesenchymal neoplasms with NTRK and other kinase gene alterations

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.     

Standardisierte Kontrastmittelsonographie (CEUS) in der klinischen Akut- und Notfallmedizin sowie Intensivmedizin (CEUS-Akut)

Die Anaesthesiologie -     

PREDICT-GTN 1: Can we improve the FIGO scoring system in gestational trophoblastic neoplasia?

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.     

Pre-COVID-19 Social Determinants of Health Among Mexican Migrants in Los Angeles and New York City and Their Increased Vulnerability to Unfavorable Health Outcomes During the COVID-19 Pandemic

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...     

滋肾育胎丸加减方预防ACA阳性者不良妊娠结局的效果及机制研究＊

目的 探讨滋肾育胎丸加减方预防抗磷脂抗体（ACA）阳性者不良妊娠结局的效果及机制研究。方法 选取2016年2月至2019年2月我院收治的89例ACA阳性，先兆性流产或有习惯性流产（RSA）史患者，将采用西医治疗的40例作为对照组，将采用西医联合滋肾育胎丸加减方治疗的49例作为观察组，比较两组中医证候疗效、中医证候积分、ACA-IgA、ACA-IgM、ACA-IgG、凝血指标［血小板聚集功能（PAF）、活化蛋白C（PC）、抗凝血酶（AT）、纤溶酶原激活抑制物-1（PAI-1）］、Th1/Th2细胞因子［干扰素γ（IFN-γ）、白介素-2（IL-2）、白介素-4（IL-4）、白介素-10（IL-10）］、妊娠结局、安全性。结果 治疗2周后检测ACA，观察组2例未降低，对照组11例未降低，观察组未降低患者占比低于对照组（P<0.05）；观察组总有效率100.00%高于对照组85.00%（P<0.05）；观察组治疗4周、7周后中医证候积分低于对照组（P<0.05）；观察组治疗4周、7周后ACA-IgA、ACA-IgM、ACA-IgG低于对照组（P<0.05）；观察组治疗4周、7周后PAF、PAI-1低于对照组，PC、AT高于对照组（P<0.05）；观察组治疗4周、7周后IFN-γ、IL-2低于对照组，IL-4、IL-10高于对照组（P<0.05）；观察组活产率95.92%高于对照组80.00%（P<0.05）；组间不良反应总发生率比较，差异无统计学意义（P>0.05）。结论 动态监测ACA对滋肾育胎丸加减方精准应用具有指导意义，指导滋肾育胎丸加减方通过调理脏腑、气血、经络功能，改善先兆性流产或有RSA史患者临床症状及凝血因子指标，降低ACA水平，并可改善患者免疫耐受功能，提高胎儿活产率，且安全性高。     

A Coupled FEM-BEM Approach for the Solution of the Free-Boundary Axi-Symmetric Plasma Equilibrium Problem

In this paper we present a coupled Finite Element Method – Boundary Element Method (FEM-BEM) approach for the solution of the free-boundary axi-symmetric plasma equilibrium problem. The proposed method, obtained from an improvement of the Hagenow-Lackner coupling method, allows to efficiently model the equilibrium problem in unbounded domains by discretizing only the plasma region; the external conductors can be modelled either as 2D or 3D models, according to the problem of interest. The paper explores different iterative methods for the solution of the nonlinear Grad-Shafranov equation, such as Picard, Newton-Raphson and Newton-Krylov, in order to provide a robust and reliable tool, able to handle large-scale problems (e.g. high resolution equilibria). This method has been implemented in the FRIDA code (FRee-boundary Integro-Differential Axisimmetric – https://github. om/matteobonotto/ FRIDA), together with a suitable Adaptive Integration Technique (AIT) for the computation of the source term. FRIDA has been successfully tested and validated against experimental data from RFX-mod device, and numerical equilibria of an ITER-like device.