Imaging-based representation and stratification of intra-tumor heterogeneity via tree-edit distance

Personalized medicine is the future of medical practice. In oncology, tumor heterogeneity assessment represents a pivotal step for effective treatment planning and prognosis prediction. Despite new procedures for DNA sequencing and analysis, non-invasive methods for tumor characterization are needed to impact on daily routine. On purpose, imaging texture analysis is rapidly scaling, holding the promise to surrogate histopathological assessment of tumor lesions. In this work, we propose a tree-based representation strategy for describing intra-tumor heterogeneity of patients affected by metastatic cancer. We leverage radiomics information extracted from PET/CT imaging and we provide an exhaustive and easily readable summary of the disease spreading. We exploit this novel patient representation to perform cancer subtyping according to hierarchical clustering technique. To this purpose, a new heterogeneity-based distance between trees is defined and applied to a case study of prostate cancer. Clusters interpretation is explored in terms of concordance with severity status, tumor burden and biological characteristics. Results are promising, as the proposed method outperforms current literature approaches. Ultimately, the proposed method draws a general analysis framework that would allow to extract knowledge from daily acquired imaging data of patients and provide insights for effective treatment planning

Estimating an individual's oxygen uptake during cycling exercise with a recurrent neural network trained from easy-to-obtain inputs: A pilot study

Measurement of oxygen uptake during exercise ([Formula: see text]) is currently non-accessible to most individuals without expensive and invasive equipment. The goal of this pilot study was to estimate cycling [Formula: see text] from easy-to-obtain inputs, such as heart rate, mechanical power output, cadence and respiratory frequency. To this end, a recurrent neural network was trained from laboratory cycling data to predict [Formula: see text] values. Data were collected on 7 amateur cyclists during a graded exercise test, two arbitrary protocols (Prot-1 and -2) and an "all-out" Wingate test. In Trial-1, a neural network was trained with data from a graded exercise test, Prot-1 and Wingate, before being tested against Prot-2. In Trial-2, a neural network was trained using data from the graded exercise test, Prot-1 and 2, before being tested against the Wingate test. Two analytical models (Models 1 and 2) were used to compare the predictive performance of the neural network. Predictive performance of the neural network was high during both Trial-1 (MAE = 229(35) mlO2min-1, r = 0.94) and Trial-2 (MAE = 304(150) mlO2min-1, r = 0.89). As expected, the predictive ability of Models 1 and 2 deteriorated from Trial-1 to Trial-2. Results suggest that recurrent neural networks have the potential to predict the individual [Formula: see text] response from easy-to-obtain inputs across a wide range of cycling intensities

Intelligent Manufacturing - Engaging Industry 4.0 Challenges through Emerging Technologies

The Industry 4.0 challenge is to exploit the synergy of different technologies in order to achieve the results required by its specifications. This chapter presents: (a) the state of the art in Augmented Reality applied to industrial engineering and manufacturing machines, (b) insights on the implementation of optimal feed-rate interpolation for computer numerical control machine tools, (c) an application of knowledge-based techniques such as computer algebra systems in the implementation of solvers for optimal control problems, and (d) challenges in the application of artificial neural networks to the massive amount of unlabeled data available in the industrial practice. It is shown how these topics, wich may appear as distant one from each other, play a central and correlated role in the Industry 4.0

Mr.CAS—A minimalistic (pure) Ruby CAS for fast prototyping and code generation

There are Computer Algebra System (CAS) systems on the market with complete solutions for manipulation of analytical models. But exporting a model that implements specific algorithms on specific platforms, for target languages or for particular numerical library, is often a rigid procedure that requires manual post-processing. This work presents a Ruby library that exposes core CAS capabilities, i.e. simplification, substitution, evaluation, etc. The library aims at programmers that need to rapidly prototype and generate numerical code for different target languages, while keeping separated mathematical expression from the code generation rules, where best practices for numerical conditioning are implemented. The library is written in pure Ruby language and is compatible with most Ruby interpreters. Keywords: CAS, Code-generation, Rub

A Hybrid Adaptive Inverse for Uncertain SISO Linear Plants with Full Relative Degree *

International audienceWe propose a hybrid adaptive feed-forward regulator for single-input single-output linear plants with full relative degree. The scheme includes an adaptive law that estimates the inverse of the plant and provides a feed-forward control calculated on the basis of the desired output and its derivatives. The adaptation is performed during discrete time events, called jumps, while the feed-forward action is continuous. This combination leads to a full hybrid system. The advantage of this framework is a conceptual separation between the adaptation dynamics, which is discrete, and the plant dynamics, which is continuous. Under an assumption of a persistence of excitation, we show through examples that the output asymptotically tracks the desired reference and that the estimate of the parameters of the inverse converges

Hypermedia navigation: Differences between spatial cognitive styles

Recently, many studies have investigated the role of individual and cognitive differences during Web navigation and Web searching. Despite this interest, no works have considered the role may assume individual differences in real-environment navigation during Web navigation. The aim of this work is to investigate the effect of different spatial cognitive styles: Landmark style (LS), Route style (RS) and Survey style (SS), on Web searching behaviour. In real-environment navigation, having a specific style determines the type of information individuals selected to navigate and orient themselves. We hypothesize that LS individuals are less proficient during Web exploration due to their analytical analysis of the environmental features. Vice versa SS individuals will show high performance on Web exploration for their holistic analysis of the World. We asked 30 College Students (10 LS, 10 RS, 10 SS) to solve three Web information tasks. The spatial cognitive style of participants was assessed through the Spatial Cognitive Style Test, and they were also asked to fill in a questionnaire about their internet and computer use. An ad hoc key-logger program for browsers was used to collect Web behaviour measures. In particular, the measures considered were: search engine tools used (e.g. back button), pages visited and revisited, time spent on information searching, and mouse cursor movements. The results showed significant differences between the spatial cognitive styles: LS seems to use a trial and error strategy in order to obtain the relevant information. Differences also emerged in the distribution of mouse cursor movements during Web navigation

Engineering the early bone metastatic niche through human vascularized immuno bone minitissues

Bone metastases occur in 65%-80% advanced breast cancer patients. Although significant progresses have been made in understanding the biological mechanisms driving the bone metastatic cascade, traditional 2Din vitromodels and animal studies are not effectively reproducing breast cancer cells (CCs) interactions with the bone microenvironment and suffer from species-specific differences, respectively. Moreover, simplifiedin vitromodels cannot realistically estimate drug anti-tumoral properties and side effects, hence leading to pre-clinical testing frequent failures. To solve this issue, a 3D metastatic bone minitissue (MBm) is designed with embedded human osteoblasts, osteoclasts, bone-resident macrophages, endothelial cells and breast CCs. This minitissue recapitulates key features of the bone metastatic niche, including the alteration of macrophage polarization and microvascular architecture, along with the induction of CC micrometastases and osteomimicry. The minitissue reflects breast CC organ-specific metastatization to bone compared to a muscle minitissue. Finally, two FDA approved drugs, doxorubicin and rapamycin, have been tested showing that the dose required to impair CC growth is significantly higher in the MBm compared to a simpler CC monoculture minitissue. The MBm allows the investigation of metastasis key biological features and represents a reliable tool to better predict drug effects on the metastatic bone microenvironment

Analizzatore di materiali per spettroscopia nelle microonde

La presente invenzione si riferisce ad un sistema per la misura di parametri, legati alle proprietà dielettriche di un materiale, utili per determinare talune caratteristiche chimico-fisiche del materiale stesso. Il sistema comprende una guida d’onda, preferibilmente rettangolare, provvista di un’apertura richiudibile per accedere all’interno della guida dove sono collocati un portacampione destinato a contenere ed alloggiare un materiale da analizzare, un’antenna trasmittente ed un’antenna ricevente poste a due lati opposti del supporto. Il sistema comprende poi un generatore di segnale a radiofrequenza operativamente connesso all’antenna trasmittente per generare un segnale radio nella guida d’onda. Il sistema comprende poi un comparatore di guadagno e fase collegato all’antenna ricevente e a quella trasmittente, per fornire all’unità di controllo il guadagno e la fase introdotti dal percorso nella guida d’onda sul segnale trasmesso dall’antenna trasmittente. L’unità di controllo provvede inoltre alla trasmissione dei dati per le necessarie elaborazioni