Primary mucinous tumors of the ovary: an interobserver reproducibility and detailed molecular study reveals significant overlap between diagnostic categories

Primary ovarian mucinous tumors represent a heterogeneous group of neoplasms, and their diagnosis may be challenging. We analyzed 124 primary ovarian mucinous tumors originally diagnosed as mucinous borderline tumors (MBTs) or mucinous carcinomas (MCs), with an emphasis on interobserver diagnostic agreement and the potential for diagnostic support by molecular profiling using a next-generation sequencing targeted panel of 727 DNA and 147 RNA genes. Fourteen experienced pathologists independently assigned a diagnosis from preset options, based on a review of a single digitized slide from each tumor. After excluding 1 outlier participant, there was a moderate agreement in diagnosing the 124 cases when divided into 3 categories (κ = 0.524, for mucinous cystadenoma vs MBT vs MC). A perfect agreement for the distinction between mucinous cystadenoma/MBT as a combined category and MC was found in only 36.3% of the cases. Differentiating between MBTs and MCs with expansile invasion was particularly problematic. After a reclassification of the tumors into near-consensus diagnostic categories on the basis of the initial participant results, a comparison of molecular findings between the MBT and MC groups did not show major and unequivocal differences between MBTs and MCs or between MCs with expansile vs infiltrative pattern of invasion. In contrast, HER2 overexpression or amplification was found only in 5.3% of MBTs and in 35.3% of all MCs and in 45% of MCs with expansile invasion. Overall, HER2 alterations, including mutations, were found in 42.2% of MCs. KRAS mutations were found in 65.5% and PIK3CA mutations in 6% of MCs. In summary, although the diagnostic criteria are well-described, diagnostic agreement among our large group of experienced gynecologic pathologists was only moderate. Diagnostic categories showed a molecular overlap. Nonetheless, molecular profiling may prove to be therapeutically beneficial in advanced-stage, recurrent, or metastatic MCs. MTG8 - Moleculaire pathologie van gynecologische tumorenMolecular tumour pathology - and tumour genetic

A Pre-Landing Assessment of Regolith Properties at the InSight Landing Site

This article discusses relevant physical properties of the regolith at the Mars InSight landing site as understood prior to landing of the spacecraft. InSight will land in the northern lowland plains of Mars, close to the equator, where the regolith is estimated to be ≥3--5 m thick. These investigations of physical properties have relied on data collected from Mars orbital measurements, previously collected lander and rover data, results of studies of data and samples from Apollo lunar missions, laboratory measurements on regolith simulants, and theoretical studies. The investigations include changes in properties with depth and temperature. Mechanical properties investigated include density, grain-size distribution, cohesion, and angle of internal friction. Thermophysical properties include thermal inertia, surface emissivity and albedo, thermal conductivity and diffusivity, and specific heat. Regolith elastic properties not only include parameters that control seismic wave velocities in the immediate vicinity of the Insight lander but also coupling of the lander and other potential noise sources to the InSight broadband seismometer. The related properties include Poisson’s ratio, P- and S-wave velocities, Young’s modulus, and seismic attenuation. Finally, mass diffusivity was investigated to estimate gas movements in the regolith driven by atmospheric pressure changes. Physical properties presented here are all to some degree speculative. However, they form a basis for interpretation of the early data to be returned from the InSight mission.Additional co-authors: Nick Teanby and Sharon Keda

Management, training and education in geotechnical engineering

This paper examines the state-of-the-art associated with the management of geotechnical data and processes; training of geotechnical engineers in the private and public sectors; and attempts to predict the future of geotechnical engineering education. The paper also explores issues related to the awareness of the importance of geotechnical engineering by owners, engineers and the public at large, and how this awareness might be enhanced in the future.M.B. Jaksa, K.K.S. Ho, M.A. Woodwar

Horizontal spatial variability of elastic modulus in sand from the dilatometer

Probabilistic modelling of soil profiles requires knowledge of three statistical parameters – the mean, standard deviation (or similar measure of the variance) and the scale of fluctuation, which provides information regarding the continuity or randomness of the soil property under investigation. The first two parameters are relatively simple to quantify, however, the third requires testing that is normally beyond the scope of the vast majority of site investigations. This paper aims to quantify the scale of fluctuation of the Young’s modulus of elasticity of a sand based on flat dilatometer tests (DMTs). Almost 500 DMTs have been performed along a horizontal line, 50 metres in total length. The horizontal interval between tests was 0.5 m, whilst the vertical spacing was 0.2 m. Random field theory and geostatistics are applied to the data in order to evaluate the scale of fluctuation. It is observed that the scale of fluctuation associated with the elastic modulus is of the order of 1.5 metres.M B Jaksa, K S Yeong, K T Wong, S L Le

Identification of sample path smoothness in soil spatial variability

Recent studies have shown that the sample path smoothness in soil spatial variability can have a significant effect on the failure probability of geotechnical problems. The purpose of the current study is to propose a procedure that can identify the sample path smoothness based on site investigation data. It is shown that two factors determine whether or not the sample path smoothness can be identified: the type of auto-correlation function (ACF) model and the parameter estimation method. In order to identify the sample path smoothness, a non-classical two-parameter ACF model, such as the powered exponential (PE) model and Whittle-Matérn (WM) model, must be adopted together with the maximum likelihood (ML) method. The method of moments (MM) is incapable of identifying the sample path smoothness regardless of the ACF model type, classical or otherwise, although it is effective in identifying the scale of fluctuation (SOF). Between the two non-classical ACF models, the WM model is more flexible because it covers a wider range of sample path smoothness than the PE model. Neither the PE model nor the WM model is able to model the “hole effect” (non-monotonic auto-correlation). The development of a sufficiently flexible non-classical model that can simultaneously identify SOF, sample path smoothness, and hole effect remains an open research question.Jianye Ching, Kok-Kwang Phoon, Armin W. Stuedlein, Mark Jaks