A decrease of calcitonin serum concentrations less than 50 percent 30 minutes after thyroid surgery suggests incomplete C-cell tumor tissue removal

The prognosis of medullary thyroid carcinoma (MTC) depends on the completeness of the first surgical treatment. To date, it is not possible to predict whether the tumor has been completely removed after surgery. The aim of this study was to evaluate the reliability of an intraoperative calcitonin monitoring as a predictor of the final outcome after surgery in patients with MTC

Ascertaining price formation in cryptocurrency markets with machine learning

The cryptocurrency market is amongst the fastest-growing of all the financial markets in the world. Unlike traditional markets, such as equities, foreign exchange and commodities, cryptocurrency market is considered to have larger volatility and illiquidity. This paper is inspired by the recent success of using machine learning for stock market prediction. In this work, we analyze and present the characteristics of the cryptocurrency market in a high-frequency setting. In particular, we applied a machine learning approach to predict the direction of the mid-price changes on the upcoming tick. We show that there are universal features amongst cryptocurrencies which lead to models outperforming asset-specific ones. We also show that there is little point in feeding machine learning models with long sequences of data points; predictions do not improve. Furthermore, we solve the technical challenge to design a lean predictor, which performs well on live data downloaded from crypto exchanges. A novel retraining method is defined and adopted towards this end. Finally, the trade-off between model accuracy and frequency of training is analyzed in the context of multi-label prediction. Overall, we demonstrate that promising results are possible for cryptocurrencies on live data, by achieving a consistent 78% accuracy on the prediction of the mid-price movement on live exchange rate of Bitcoins vs. US dollars

Explaining the neural activity distribution associated with discrete movement sequences:Evidence for parallel functional systems

To explore the effects of practice we scanned participants with fMRI while they were performing four-key unfamiliar and familiar sequences, and compared the associated activities relative to simple control sequences. On the basis of a recent cognitive model of sequential motor behavior (C-SMB), we propose that the observed neural activity would be associated with three functional networks that can operate in parallel and that allow (a) responding to stimuli in a reaction mode, (b) sequence execution using spatial sequence representations in a central-symbolic mode, and (c) sequence execution using motor chunk representations in a chunking mode. On the basis of this model and findings in the literature, we predicted which neural areas would be active during execution of the unfamiliar and familiar keying sequences. The observed neural activities were largely in line with our predictions, and allowed functions to be attributed to the active brain areas that fit the three above functional systems. The results corroborate C-SMB’s assumption that at advanced skill levels the systems executing motor chunks and translating key-specific stimuli are racing to trigger individual responses. They further support recent behavioral indications that spatial sequence representations continue to be used

A role for nuclear stretching and NPCs changes in the cytoplasmic-nuclear trafficking of YAP: An experimental and numerical modelling approach

Mechanical forces, acting on eukaryotic cells, are responsible for cell shape, cell proliferation, cell polarity, and cell differentiation thanks to two cells abilities known as mechanosensing and mechanotransduction. Mechanosensing consists of the ability of a cell to sense mechanical cues, while mechanotransduction is the capacity of a cell to respond to these signals by translating mechanical stimuli into biochemical ones. These signals propagate from the extracellular matrix to the nucleus with different well known physical connections, but how the mechanical signals are transduced into biochemical ones remains an open challenge. Recent findings showed that the cell-generated forces affect the translocation of transcription factors (TFs) from the cytoplasm to the nucleus. This mechanism is affected by the features of nuclear pore complexes. Owing to the complex patterns of strains and stresses of the nuclear envelope caused by cytoskeletal forces, it is likely that the morphology of NPC changes as cytoskeleton assemblies’ change. This may ultimately affect molecular transport through the nucleus, hence altering cell functions. Among the various TFs, Yes-associated protein (YAP), which is typically involved in cell proliferation, survival, and differentiation, is able to activate specific pathways when entrapped into the cell nucleus. Here, starting from experimental results, we develop a multiscale finite element (FE) model aimed to simulate the macroscopic cell spreading and consequent changes in the cell mechanical behaviour to be related to the NPCs changes and YAP nuclear transport

Analysis of dynamic wireless power transfer systems based on behavioral modeling of mutual inductance

This paper proposes a system-level approach suitable to analyze the performance of a dynamic Wireless Power Transfer System (WPTS) for electric vehicles, accounting for the uncertainty in the vehicle trajectory. The key-point of the approach is the use of an analytical behavioral model that relates mutual inductance between the coil pair to their relative positions along the actual vehicle trajectory. The behavioral model is derived from a limited training data set of simulations, by using a multi-objective genetic programming algorithm, and is validated against experimental data, taken from a real dynamic WPTS. This approach avoids the massive use of computationally expensive 3D finite element simulations, that would be required if this analysis were performed by means of look-up tables. This analytical model is here embedded into a system-level circuital model of the entire WPTS, thus allowing a fast and accurate analysis of the sensitivity of the performance as the actual vehicle trajectory deviates from the nominal one. The system-level analysis is eventually performed to assess the sensitivity of the power and efficiency of the WPTS to the vehicle misalignment from the nominal trajectory during the dynamic charging process