Risk Assessment for Venous Thromboembolism in Chemotherapy-Treated Ambulatory Cancer Patients: A Machine Learning Approach

OBJECTIVE: To design a precision medicine approach aimed at exploiting significant patterns in data, in order to produce venous thromboembolism (VTE) risk predictors for cancer outpatients that might be of advantage over the currently recommended model (Khorana score). DESIGN: Multiple kernel learning (MKL) based on support vector machines and random optimization (RO) models were used to produce VTE risk predictors (referred to as machine learning [ML]-RO) yielding the best classification performance over a training (3-fold cross-validation) and testing set. RESULTS: Attributes of the patient data set ( n = 1179) were clustered into 9 groups according to clinical significance. Our analysis produced 6 ML-RO models in the training set, which yielded better likelihood ratios (LRs) than baseline models. Of interest, the most significant LRs were observed in 2 ML-RO approaches not including the Khorana score (ML-RO-2: positive likelihood ratio [+LR] = 1.68, negative likelihood ratio [-LR] = 0.24; ML-RO-3: +LR = 1.64, -LR = 0.37). The enhanced performance of ML-RO approaches over the Khorana score was further confirmed by the analysis of the areas under the Precision-Recall curve (AUCPR), and the approaches were superior in the ML-RO approaches (best performances: ML-RO-2: AUCPR = 0.212; ML-RO-3-K: AUCPR = 0.146) compared with the Khorana score (AUCPR = 0.096). Of interest, the best-fitting model was ML-RO-2, in which blood lipids and body mass index/performance status retained the strongest weights, with a weaker association with tumor site/stage and drugs. CONCLUSIONS: Although the monocentric validation of the presented predictors might represent a limitation, these results demonstrate that a model based on MKL and RO may represent a novel methodological approach to derive VTE risk classifiers. Moreover, this study highlights the advantages of optimizing the relative importance of groups of clinical attributes in the selection of VTE risk predictors

Analytical and experimental shear evaluation of GFRP-reinforced concrete beams

Reinforced Concrete (RC) technology is advancing towards new frontiers enhancing its sustainability and durability through innovative materials. In particular, the application of Glass Fiber Reinforced Polymer (GFRP) bars, in lieu of steel reinforcement, shows excellent performance, especially in aggressive environments. Nevertheless, current international design guidelines and standards tend to be rather conservative, especially concerning shear reinforcement. This element hinders the technology’s competitiveness, not only in terms of material consumption but also in construction efficiency. This research aims to conduct an analytical comparison and experimental validation of the formulations found in some international standards pertaining to shear capacity in a specific case. The focus is on scenarios involving reduced shear reinforcement and cases where the number of stirrups falls below the minimum recommended by these standards. In the sample beam tests, two distinct flexural GFRP reinforcement ratios were employed to evaluate their influence on shear capacity, leading to diverse failure mechanisms: rupture of longitudinal GFRP bars and concrete crushing. The experimental results were used to compare the North American ACI, French AFGC, and Italian CNR shear capacity design approaches in the case of reduced transversal reinforced ratio. Analytical capacity expressions of the standards above are discussed with some remarks aiming at structural optimization

Ensuring sample quality for biomarker discovery studies - Use of ict tools to trace biosample life-cycle

The growing demand of personalized medicine marked the transition from an empirical medicine to a molecular one, aimed at predicting safer and more effective medical treatment for every patient, while minimizing adverse effects. This passage has emphasized the importance of biomarker discovery studies, and has led sample availability to assume a crucial role in biomedical research. Accordingly, a great interest in Biological Bank science has grown concomitantly. In biobanks, biological material and its accompanying data are collected, handled and stored in accordance with standard operating procedures (SOPs) and existing legislation. Sample quality is ensured by adherence to SOPs and sample whole life-cycle can be recorded by innovative tracking systems employing information technology (IT) tools for monitoring storage conditions and characterization of vast amount of data. All the above will ensure proper sample exchangeability among research facilities and will represent the starting point of all future personalized medicine-based clinical trials

Investigation into the Influence of the Process Parameters on the Stability of a Poly(Vinyl)-Alcohol-Based Coating System

Most tablets put on the market are coated with polymers soluble in water. The Opadry II 85 series from Colorcon Inc., is a family of PVA-based products marketed since the 1990s. Despite numerous publications on the properties of PVA, to date, limited work has been undertaken to determine the physico-chemical parameters (i.e., UV light, high temperature, and relative humidity) that could affect the performance of PVA-based coatings. To this end, we performed artificial ageing processes on samples made of Opadry Orange II or of some selected components of this coating and analysed them by means of a multidisciplinary approach, using, for example, FTIR, NMR, rheology, and DMTA measurements. In this way, we analysed the influence of the critical components of the Opadry Orange II formula, such as titanium dioxide and aluminium hydroxide, on the coating characteristics under ageing conditions

Compatibilization of an immiscible blend of EPDM and POM with an Ionomer

Immiscible blends of ethylene‐propylene‐diene‐monomer (EPDM) and polyoxymethylene (POM), when EPDM is the major phase were compatibilized on the addition of an ionomer, poly(ethylene‐co‐methacrylic acid). The inclusion of the ionomer reduced the interfacial tension between the two phases, such that the diameter of the POM domains were significantly reduced to between 0.5 and 2 μm, typical of that required to toughen ductile polymers. The mechanical properties of the resultant compatibilized blends were significantly enhanced with increases in Young's modulus (↑54%), tensile strength (σ, ↑139%), elongation at break (ε, ↑97%), and tensile toughness (↑500%) with increasing ionomer content, relative to EPDM rubber alone. The ShoreA hardness of the compatibilized blend was 70.1 compared with 56.8 for the immiscible binary blend and, 50.2 for neat EPDM rubber

Nano-topography Enhances Communication in Neural Cells Networks

Abstract Neural cells are the smallest building blocks of the central and peripheral nervous systems. Information in neural networks and cell-substrate interactions have been heretofore studied separately. Understanding whether surface nano-topography can direct nerve cells assembly into computational efficient networks may provide new tools and criteria for tissue engineering and regenerative medicine. In this work, we used information theory approaches and functional multi calcium imaging (fMCI) techniques to examine how information flows in neural networks cultured on surfaces with controlled topography. We found that substrate roughness S a affects networks topology. In the low nano-meter range, S a  = 0–30 nm, information increases with S a . Moreover, we found that energy density of a network of cells correlates to the topology of that network. This reinforces the view that information, energy and surface nano-topography are tightly inter-connected and should not be neglected when studying cell-cell interaction in neural tissue repair and regeneration

The effect of social media and infodemic on mental health during the COVID-19 pandemic: results from the COMET multicentric trial

On January 30, 2020, the World Health Organization (WHO) declared the status of pandemic due to the COVID-19 infection. The initial phases of the pandemic were characterized by uncertainty and public fears. In order to cope with such unexpected conditions, people adopted different coping strategies, including search for information, accessing Internet, and using social media. The present study based on the COMET collaborative research network aims to: (1) assess use of Internet and of social media among the Italian general population; (2) explore differences in web usage between people with pre-existing mental disorders and the general population; (3) identify changes over time in social media usage along the phase 1 of the pandemic; (4) identify the clinical, socio-demographic and contextual predictors of excessive use of social media. A significant increase in time spent on Internet, with an average time of 4.8 ± 0.02 h per day, was found in the global sample of 20,720 participants. Compared with the general population, Internet use was significantly higher in people with pre-existing mental disorders (5.2 ± 0.1 h vs. 4.9 ± 0.02; p < 0.005). According to the multivariate logistic regression model, the risk of excessive use of social media and Internet was significantly higher in people with moderate levels of depressive symptoms (OR: 1.26, CI 95%: 0.99 to 1.59, p < 0.0.005); while protective factors were being students (OR: 0.72, CI 95%: 0.53 to 0.96, p < 0.0029) and living in central Italy (OR: 0.46, CI 95%: 0.23 to 0.90, p < 0.002). The evaluation of social media and Internet use by the general population represents a first step for developing specific protective and supportive interventions for the general population, including practical suggestions on how to safely use Internet and social media

COVID-19-Related Social Isolation Predispose to Problematic Internet and Online Video Gaming Use in Italy

COVID-19 pandemic and its related containment measures have been associated with increased levels of stress, anxiety and depression in the general population. While the use of digital media has been greatly promoted by national governments and international authorities to maintain social contacts and healthy lifestyle behaviors, its increased access may also bear the risk of inappropriate or excessive use of internet-related resources. The present study, part of the COVID Mental hEalth Trial (COMET) study, aims at investigating the possible relationship between social isolation, the use of digital resources and the development of their problematic use. A cross sectional survey was carried out to explore the prevalence of internet addiction, excessive use of social media, problematic video gaming and binge watching, during Italian phase II (May-June 2020) and III (June-September 2020) of the pandemic in 1385 individuals (62.5% female, mean age 32.5 +/- 12.9) mainly living in Central Italy (52.4%). Data were stratified according to phase II/III and three groups of Italian regions (northern, central and southern). Compared to the larger COMET study, most participants exhibited significant higher levels of severe-to-extremely-severe depressive symptoms (46.3% vs. 12.4%; p &lt; 0.01) and extremely severe anxiety symptoms (77.8% vs. 7.5%; p &lt; 0.01). We also observed a rise in problematic internet use and excessive gaming over time. Mediation analyses revealed that COVID-19-related general psychopathology, stress, anxiety, depression and social isolation play a significant role in the emergence of problematic internet use, social media addiction and problematic video gaming. Professional gamers and younger subjects emerged as sub-populations particularly at risk of developing digital addictions. If confirmed in larger and more homogenous samples, our findings may help in shedding light on possible preventive and treatment strategies for digital addictions

Citric acid aerospace stainless steel passivation: a green approach

Passivation is a common treatment to maximize the corrosion resistance of stainless steel. Nitric acid is generally used and involves several ecological problems, citric acid could be a promising and environmentally friendly alternative to nitric acid. In this work citric acid has been extracted from lemon waste using and eco- friendly procedure. The stainless steel samples have been treated in both nitric and citric acid (commercial and extracted) and corrosion test have been performed. The results show how citric acid can be used as substitute of nitric acid in passivation treatment