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We present a new method for the stable reconstruction of a class of binary images from a small number of measurements. The images we consider are characteristic functions of algebraic domains, that is, domains defined as zero loci of bivariate polynomials, and we assume to know only a finite set of uniform samples for each image. The solution to such a problem can be set up in terms of linear equations associated to a set of image moments. However, the sensitivity of the moments to noise makes the numerical solution highly unstable. To derive a robust image recovery algorithm, we represent algebraic polynomials and the corresponding image moments in terms of bivariate Bernstein polynomials and apply polynomial-generating, refinable sampling kernels. This approach is robust to noise, computationally fast and simple to implement. We illustrate the performance of our reconstruction algorithm from noisy samples through extensive numerical experiments. Our code is released open source and freely available.

Chronic pain is one of the most common and critical long-term effects of breast cancer. Digital health technologies enhance the management of chronic pain by monitoring physical and psychological health status and supporting pain self-management and patient treatment decisions throughout the clinical pathway. This pilot study aims to evaluate patients' experiences, including usability, with a novel digital integrated health ecosystem for chronic pain named PainRELife. The sample included patients with breast cancer during survivorship. The PainRELife ecosystem comprises a cloud technology platform interconnected with electronic health records and patients' devices to gather integrated health care data. We enrolled 25 patients with breast cancer (mean age 47.12 years) experiencing pain. They were instructed to use the PainRELife mobile app for 3 months consecutively. The Mobile Application Rating Scale (MARS) was used to evaluate usability. Furthermore, pain self-efficacy and participation in treatment decisions were evaluated. The study received ethical approval (R1597/21-IEO 1701) from the Ethical Committee of the European Institute of Oncology. The MARS subscale scores were medium to high (range: 3.31-4.18), and the total app quality score was 3.90. Patients with breast cancer reported reduced pain intensity at 3 months, from a mean of 5 at T0 to a mean of 3.72 at T2 (P=.04). The total number of times the app was accessed was positively correlated with pain intensity at 3 months (P=.03). The engagement (P=.03), information (P=.04), and subjective quality (P=.007) subscales were positively correlated with shared decision-making. Furthermore, participants with a lower pain self-efficacy at T2 (mean 40.83) used the mobile app more than participants with a higher pain self-efficacy (mean 48.46; P=.057). The data collected in this study highlight that digital health technologies, when developed using a patient-driven approach, might be valuable tools for increasing participation in clinical care by patients with breast cancer, permitting them to achieve a series of key clinical outcomes and improving quality of life. Digital integrated health ecosystems might be important tools for improving ongoing monitoring of physical status, psychological burden, and socioeconomic issues during the cancer survivorship trajectory. RR2-10.2196/41216.

Chronic pain (CP) and its management are critical issues in the care pathway of patients with breast cancer. Considering the complexity of CP experience in cancer, the international scientific community has advocated identifying cutting-edge approaches for CP management. Recent advances in the field of health technology enable the adoption of a novel approach to care management by developing integrated ecosystems and mobile health apps. The primary end point of this pilot study is to evaluate patients' usability experience at 3 months of a new digital and integrated technological ecosystem, PainRELife, for CP in a sample of patients with breast cancer. The PainRELife ecosystem is composed of 3 main technological assets integrated into a single digital ecosystem: Fast Healthcare Interoperability Resources-based cloud platform (Nu platform) that enables care pathway definition and data collection; a big data infrastructure connected to the Fast Healthcare Interoperability Resources server that analyzes data and implements dynamic dashboards for aggregate data visualization; and an ecosystem of personalized applications for patient-reported outcomes collection, digital delivery of interventions and tailored information, and decision support of patients and caregivers (PainRELife app). This is an observational, prospective pilot study. Twenty patients with early breast cancer and chronic pain will be enrolled at the European Institute of Oncology at the Division of Medical Senology and the Division of Pain Therapy and Palliative Care. Each patient will use the PainRELife mobile app for 3 months, during which data extracted from the questionnaires will be sent to the Nu Platform that health care professionals will manage. This pilot study is nested in a large-scale project named \"PainRELife,\" which aims to develop a cloud technology platform to interoperate with institutional systems and patients' devices to collect integrated health care data. The study received approval from the Ethical Committee of the European Cancer Institute in December 2021 (number R1597/21-IEO 1701). The recruitment process started in May 2022 and ended in October 2022. The new integrated technological ecosystems might be considered an encouraging affordance to enhance a patient-centered approach to managing patients with cancer. This pilot study will inform about which features the health technological ecosystems should have to be used by cancer patients to manage CP. DERR1-10.2196/41216.

In this paper we focus on Hermite subdivision operators that act on vector valued data interpreting their components as function values and associated consecutive derivatives. We are mainly interested in studying the exponential and polynomial preservation capability of such kind of operators, which can be expressed in terms of a generalization of the spectral condition property in the spaces generated by polynomials and exponential functions. The main tool for our investigation are convolution operators that annihilate the aforementioned spaces, which apparently is a general concept in the study of various types of subdivision operators. Based on these annihilators, we characterize the spectral condition in terms of factorization of the subdivision operator.

Within the nutritionism paradigm, in this article we critically review the marketization and medicalization logics which aim to address the pressing issue of malnutrition in low- and middle-income countries. Drawing from political economy and food system transformation discourses, we are using the popular intervention types of nutrition-sensitive value chains (marketization logic) and biofortification exemplified through orange-fleshed sweet potato (medicalization logic) to assess their outcomes and underlying logics. We demonstrate that there is insufficient evidence of the positive impact of these interventions on nutritional outcomes, and that their underlying theories of change and impact logics do not deal with the inherent complexity of nutritional challenges. We show that nutrition-sensitive value chain approaches are unable to leverage or enhance the functioning of value chains to improve nutritional outcomes, especially in light of the disproportionate power of some food companies. We further demonstrate that orange-fleshed sweet potato interventions and biofortification more broadly adopt a narrow approach to malnutrition, disregarding the interactions between food components and broader value chain and food system dynamics. We argue that both intervention types focus solely on increasing the intake of specific nutrients without incorporating their embeddedness in the wider food systems and the relevant political-economic and social relations that influence the production and consumption of food. We conclude that the systemic nature of malnutrition requires to be understood and addressed as part of the food system transformation challenge in order to move towards solving it. To do so, new evaluation frameworks along with new approaches to solutions are necessary that support multiple and diverse development pathways, which are able to acknowledge the social, political-economic, and environmental factors and drivers of malnutrition and poverty.

Convergence and normal continuity analysis of a bivariate nonstationary (level-dependent) subdivision scheme for 2-manifold meshes with arbitrary topology is still an open issue. Exploiting ideas from the theory of asymptotically equivalent subdivision schemes, in this paper we derive new sufficient conditions for establishing convergence and normal continuity of any rotationally symmetric, nonstationary subdivision scheme near an extraordinary vertex/face.

Cardio-renal syndrome is a clinical condition that has recently been well defined. In acute kidney disease, this interaction might trigger chronic processes determining the onset of cardiovascular events and the progression of chronic kidney disease. Moreover, the high mortality rate of acute kidney injury (AKI) is also linked to the fact that this condition is often complicated by dysfunctions of other organs such as lungs or heart, or is associated with septic episodes. In this context the role and the potential link between bone, heart and kidney is becoming an important topic of research. The aim of this review is to describe the cardiac alterations in the presence of AKI (cardiorenal syndrome type 3) and explore how bone can interact with heart and kidney in determining and influencing the trend of AKI in the short and long term. The main anomalies of mineral metabolism in patients with AKI will be reported, with specific reference to the alterations of fibroblast growth factor 23 and Klotho as a link between the bone–kidney–heart axis. Lay Summary In this review the cardiac involvement and the interaction between bone, heart and kidney in the presence of acute kidney injury (AKI) are reported. This is a “hot topic” in nephrology research. In fact some evidence demonstrates a potential role for fibroblast growth factor 23, produced in the bone, and Klotho in modulating the inflammation, in endothelial dysfunction and in promoting cardiovascular risk in AKI settings. We think that this review underlines this relationship in a simple way, opening up future research. Graphical Abstract Graphical Abstract

IntroductionAfter several years of brain-sensing technology development and proof-of-concept studies, adaptive deep brain stimulation (aDBS) is ready to better treat Parkinson’s disease (PD) using aDBS-capable implantable pulse generators (IPGs). New aDBS devices are capable of continuous sensing of neuronal activity from the subthalamic nucleus (STN) and contemporaneous stimulation automatically adapted to match the patient’s clinical state estimated from the analysis of STN activity using proprietary algorithms. Specific studies are necessary to assess superiority of aDBS vs conventional DBS (cDBS) therapy. This protocol describes an original innovative multicentre international study aimed to assess safety and efficacy of aDBS vs cDBS using a new generation of DBS IPG in PD (AlphaDBS system by Newronika SpA, Milan, Italy).MethodsThe study involves six investigational sites (in Italy, Poland and The Netherlands). The primary objective will be to evaluate the safety and tolerability of the AlphaDBS System, when used in cDBS and aDBS mode. Secondary objective will be to evaluate the potential efficacy of aDBS. After eligibility screening, 15 patients with PD already implanted with DBS systems and in need of battery replacement will be randomised to enter a two-phase protocol, including a ‘short-term follow-up’ (2 days experimental sessions during hospitalisation, 1 day per each mode) and a ‘long-term follow-up’ (1 month at home, 15 days per each mode).Ethics and disseminationThe trial was approved as premarket study by the Italian, Polish, and Dutch Competent Authorities: Bioethics Committee at National Oncology Institute of Maria Skłodowska-Curie—National Research Institute in Warsaw; Comitato Etico Milano Area 2; Comitato Etico IRCCS Istituto Neurologico C. Besta; Comitato Etico interaziendale AOUC Città della Salute e della Scienza—AO Ordine Mauriziano di Torino—ASL Città di Torino; De Medisch Ethisch Toetsingscommissie van Maastricht UMC. The study started enrolling patients in January 2021.Trial registration numberNCT04681534.

In this paper we describe a general, computationally feasible strategy to deduce a family of interpolatory non-stationary subdivision schemes from a symmetric non-stationary, non-interpolatory one satisfying quite mild assumptions. To achieve this result we extend our previous work (Conti et al., Linear Algebra Appl 431(10):1971–1987, 2009) to full generality by removing additional assumptions on the input symbols. For the so obtained interpolatory schemes we prove that they are capable of reproducing the same space of exponential polynomials as the one generated by the original approximating scheme. Moreover, we specialize the computational methods for the case of symbols obtained by shifted non-stationary affine combinations of exponential B-splines, that are at the basis of most non-stationary subdivision schemes. In this case we find that the associated family of interpolatory symbols can be determined to satisfy a suitable set of generalized interpolating conditions at the set of the zeros (with reversed signs) of the input symbol. Finally, we discuss some computational examples by showing that the proposed approach can yield novel smooth non-stationary interpolatory subdivision schemes possessing very interesting reproduction properties.