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Cancer risks by sex and variant type in PTEN Hamartoma Tumor Syndrome
No full textBACKGROUND: PTEN Hamartoma Tumor Syndrome (PHTS) is a rare syndrome with a broad phenotypic spectrum, including increased risks of breast (BC, 67-78% at age 60), endometrial (EC, 19-28%) and thyroid cancer (TC, 6-38%). Current risks are likely overestimated due to ascertainment bias. We aimed to provide more accurate and personalized cancer risks. METHODS: A European, adult PHTS cohort study with data from medical files, registries and/or questionnaires. Cancer risks and hazard ratios were assessed with Kaplan-Meier and Cox regression analyses, and standardized incidence ratios (SIR) were calculated. Bias correction consisted of excluding cancer index cases and incident case analyses. RESULTS: 455 patients were included, including 50.5% index cases, 372 with prospective follow-up (median 6 year, IQR:3-10), and 159/281 females and 39/174 males with cancer. By age 60, PHTS-related cancer risk was higher in females (68.4% to 86.3%) than males (16.4% to 20.8%). Female BC risks ranged from 54.3% (95%CI 43.0-66.4) to 75.8% (95%CI 60.7-88.4), with two-to-three-fold increased risks for PTEN truncating and about two-fold for phosphatase domain variants. EC risks ranged from 6.4% (95%CI 2.1-18.6) to 22.1% (95%CI 11.6-39.6), and TC risks from 8.9% (95%CI 5.1-15.3) to 20.5% (95%CI 11.3-35.4). Colorectal cancer, renal cancer and melanoma risks were each below 10.0%. CONCLUSION: Females have a different breast cancer risk depending on their PTEN germline variant. PHTS patients are predominantly at risk of breast (females), endometrial and thyroid cancer. This should be the main focus of surveillance. These lower, more unbiased and personalized risks provide guidance for optimized cancer risk management
Embodied Attention in Word-Object Mapping: A Developmental Cognitive Robotics Model
No full textDevelopmental Robotics models provide useful tools to study and understand the language learning process in infants and robots. These models allow us to describe key mechanisms of language development, such as statistical learning, the role of embodiment, and the impact of the attention payed to an object while learning its name. Robots can be particularly well suited for this type of problems, because they cover both a physical manipulation of the environment and mathematical modeling of the temporal changes of the learned concepts. In this work we present a computational representation of the impact of embodiment and attention on word learning, relying on sensory data collected with a real robotic agent in a real world scenario. Results show that the cognitive architecture designed for this scenario is able to capture the changes underlying the moving object in the field of view of the robot. The architecture successfully handles the temporal relationship in moving items and manages to show the effects of the embodied attention on word-object mapping
A Proof System for Cyber-physical Systems with Shared-Variable Concurrency
No full textCyber-physical system (CPS) is about the interplay of discrete behaviors and continuous behaviors. The combination of the physical and the cyber may cause hardship for the modeling and verication of CPS. Hence, a language based on shared variables was proposed to realize the interaction in CPS. In this paper, we formulate a proof system for this language. To handle the parallel composition with shared variables, we extend classical Hoare triples and bring the trace model into our proof system. The introduction of the trace may complicate ourspecication slightly, but it can realize a compositional proof when the program is executing. Meanwhile, this introduction can set up a bridge between our proof system and denotational semantics. Throughout this paper, we also present some examples to illustrate the usage of our proof system intuitively.Keywords: Cyber-physical System (CPS) · Shared Variables · Trace Model · Hoare Logic
Time restricted feeding – a free and effective method of managing hypertension by ameliorating inflammation?
No full textLatent class trajectory modelling: impact of changes in model specification
No full textLatent class trajectory models (LCTMs) are often used to identify subgroups of patients that are clinically meaningful in terms of longitudinal exposure and out¬come, e.g. drug response patterns. These models are increasingly applied in medicine and epidemiology. However, in many published studies, it is not clear whether the chosen models, where subgroups of patients are identified, represent real heterogeneity in the population, or whether any associations with clinically meaningful characteristics are accidental. In particular, we note an apparent over-reliance on lowest AIC or BIC values. While these are objective measures of goodness of fit, that can help identify the optimal number of subgroups, they are not sufficient on their own to fully evaluate a given trajectory model. Here we demonstrate how longitudinal latent class models can substantially change by making small modification in model specification, and the potential impact of this on the relationship to clinical outcomes. We show that the predicted trajectory patterns and outcome probabilities differ when pre-specified cubic versus linear shapes are tested on the same data. However, both could be interpreted to be the “correct” model. We emphasise that LCTMs, as all unsupervised approaches, are hypotheses generating, and should not be directly implemented in clinical practice without significant testing and validation
Some Effects of Surface Finish and LWR Environment on Environmentally-assisted Crack Initiation in Alloy 182
No full textWithin the European Commission funded project MEACTOS, environmentally-assisted crack (EAC) initiation of Alloy 182 was addressed by performing constant extension rate tensile (CERT) and constant load (CL) testing of flat, tapered tensile specimens in both boiling water reactor (BWR) normal water chemistry (NWC) and pressurized water reactor (PWR) primary water environment. Four surface finishes were investigated, namely: ground which serves as reference (RS), industrial face-milled (STI), advanced-machined (SAM) and two shot peened conditions (SP, initial and later). After testing the critical stress for initiating a crack was derived by locating the critical section (the border between areas showing and not showing surface cracking after testing) and calculating the associated local stress. In a first analysis of the CERT results, the critical stress was plotted against the nominal strain rate (cross-head displacement rate divided by the length of the tapered gauge section) and an exponential curve was fitted to it; yielding a characteristic critical stress (extrapolation to zero nominal strain rate) and a characteristic nominal strain rate (rendering the nominal strain rate dimensionless under the exponent). In a second analysis of the CERT results, an initiation model, which is strain rate and stress level dependent, was fitted to obtain a usage towards EAC initiation of 1 in the experimentally-determined critical cross section. CL testing was performed under the same and accelerated test conditions, achieved by increasing temperature and changing test environment. The overall conclusion is that (1) EAC initiation performance is better in the BWR/NWC than in the PWR environment, (2) effects of surface finish are more clearly visible in the PWR environment, (3) EAC initiation performance is better for SAM than for RS or STI which are similar and in turn better than the original SP. A “higher quality” SP surface showed an improvement in EAC initiation performance and this correlated well with the lower surface hardness measured for the latter meaning that hardness could be used as a measure for the quality of surface treatments in respect of EAC initiation
Mitochondrial antiviral-signalling protein is a client of the BAG6 protein quality control complex
No full textThe heterotrimeric BAG6 complex coordinates the direct handover of newly synthesised tail-anchored (TA) membrane proteins from an SGTA-bound preloading complex to the endoplasmic reticulum (ER) delivery component TRC40. In contrast, defective precursors, including aberrant TA proteins, form a stable complex with this cytosolic protein quality control factor, enabling such clients to be either productively re-routed or selectively degraded. We identify the mitochondrial TA protein MAVS (mitochondrial antiviral-signalling protein) as an endogenous client of both SGTA and the BAG6 complex. Our data suggest that the BAG6 complex binds to a cytosolic pool of MAVS before its misinsertion into the ER membrane, from where it can subsequently be removed via ATP13A1-mediated dislocation. This BAG6- associated fraction of MAVS is dynamic and responds to the activation of an innate immune response, suggesting that BAG6 may modulate the pool of MAVS that is available for coordinating the cellular response to viral infection
Stein factors for variance-gamma approximation in the Wasserstein and Kolmogorov distances
No full textWe obtain new bounds for the solution of the variance-gamma (VG) Stein equation that are of the correct form for approximations in terms of the Wasserstein and Kolmorogorov metrics. These bounds hold for all parameters values of the four parameter VG class. As an application we obtain explicit Wasserstein and Kolmogorov distance error bounds in a six moment theorem for VG approximation of double Wiener-It^o integrals
THE DEVELOPMENT OF A NEW METHOD TO COMPARE THE FATIGUE CRACK GROWTH RATES OF AUSTENITIC STAINLESS STEEL OPERATING IN A PWR PRIMARY COOLANT SUBJECTED TO PLANT REALISTIC TEMPERATURE LOADING
No full textFatigue Crack Growth Rates (FCGRs) of austenitic stainless steels can be significantly enhanced when tested in a high temperature water environment compared to those tested in air. Existing FCGR models are based on simple isothermal waveform loading. Recent work has highlighted that there may be a potential benefit into taking account of plant realistic loading waveforms in fatigue assessments as these may be less damaging than predict ions based on simple loading conditions. As a result, new methods to account for these plant realistic loads have been developed to reduce excess conservatism of existing methods for predicting FCGRs.To provide confidence in these methods, a previous UK thermomechanical fatigue testing program me has been conducted on Compact Tension (C(T)) specimens subjected to plant realistic loads, with the crack length and Crack Growth Rates CGRs being monitored in situ using the Direct Current Potential Drop (DCPD) technique. This paper utilizes three different methodologies to evaluate the CGR of samples that underwent corrosion fatigue in different conditions namely; DCPD, post mortem measurement of crack advance using Scanning Electron Microscopy (SEM) and the measurement of the spacing between striations to infer CGR.It was found that DCPD provided a good global average of FCGRs at the crack front but does not capture local changes associated with the local microstructureOverall, it was shown that post mortem examination for stage measurements can be reliably applied to infer CGR on samples that were not instrumented with DCP