Time-resolved prompt-gamma activation analysis at spallation neutron sources and applications to cultural heritage, security, and radiation protection

Abstract The present and future developments of time-resolved prompt-gamma activation analysis (T-PGAA) at pulsed neutron sources is discussed in the framework of the successful history of neutron-activation techniques. A brief description of the state of the art and the most important user facilities using standard prompt-gamma activation analysis (PGAA) is provided. Then, we discuss the challenges and the opportunities for T-PGAA at pulsed neutron sources, and the potential impact for applications to cultural heritage, radiation protection, and security. We notice some inversions of trend needed for the further development of T-PGAA with epithermal and fast neutrons, such as the possibility to use fast and high-efficiency γ-ray scintillators with lower energy resolution (compared to usual high-purity germanium detectors) when the signal from neutron capture resonance is selected. We also suggest how detection systems often used in other fields, such as medical physics, can be of interest and inspiration also in the case of neutron-based investigations. Finally, we present new data of T-PGAA measurements on VESUVIO using neutron energies up to the keV using the scintillators available on the instrument, for samples of gold (of interest in cultural heritage), cadmium (for environmental safety), and tantalum (a material used in biomedical implants)

Alteration of microRNAs regulated by c-Myc in burkitt lymphoma

Background: Burkitt lymphoma (BL) is an aggressive B-cell lymphoma, with a characteristic clinical presentation, morphology and immunophenotype. Over the past years, the typical translocation t(8;14) and its variants have been considered the molecular hallmark of this tumor. However, BL cases with no detectable MYC rearrangement have been identified. Intriguingly, these cases express MYC at levels comparable with cases carrying the translocation. In normal cells c-Myc expression is tightly regulated through a complex feedback loop mechanism. In cancer, MYC is often dysregulated, commonly due to genomic abnormalities. It has recently emerged that this phenomenon may rely on an alteration of post-transcriptional regulation mediated by microRNAs (miRNAs), whose functional alterations are associated with neoplastic transformation. It is also emerging that c-Myc modulates miRNA expression, revealing an intriguing crosstalk between c-Myc and miRNAs. Principal Findings: Here, we investigated the expression of miRNAs possibly regulated by c-Myc in BL cases positive or negative for the translocation. A common trend of miRNA expression, with the exception of hsa-miR-9*, was observed in all of the cases. Intriguingly, down-regulation of this miRNA seems to specifically identify a particular subset of BL cases, lacking MYC translocation. Here, we provided evidence that hsa-miR-9-1 gene is heavily methylated in those cases. Finally, we showed that hsa-miR-9* is able to modulate E2F1 and c-Myc expression. Conclusions: Particularly, this study identifies hsa-miR-9* as potentially relevant for malignant transformation in BL cases with no detectable MYC translocation. Deregulation of hsa-miR-9* may therefore be useful as a diagnostic tool, suggesting it as a promising novel candidate for tumor cell marker

L’APP Mind Inclusion: la tecnologia assistiva per promuovere l’inclusione sociale delle persone con disabilità intelletive nella loro comunità

Information and Communication Technologies have been widely used to enhance evidencebased interventions in the education and training of individuals with intellectual disabilities. The use of Information and Communication Technologies for these purposes is called Assistive Technology. Assistive technology is able to support persons with intellectual disabilities to live fuller and richer lives in their communities, supporting more successful functioning across multiple domains: independent living and inclusion in community.This study has the aim to present and explain the development of an assistive technology tool for persons with intellectual disabilities, the Mind Inclusion APP which can allow persons with intellectual disabilities to search and reach for a location or an activity in their community. The APP was co-created through the support of a participatory design and a person centred approach.A sample of 48 people, including persons with disabilities, caregivers, educators and business owners, was involved at all stages of the project. This study has shown that persons with disabilities can interact better, be part of their society more easily, and learn new skills reducing the impact of disability on daily functioning by using the Mind Inclusion APP

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Peer Reviewe

Gamma background characterization on VESUVIO: before and after the moderator upgrade

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Multicenter clinical assessment of improved wearable multimodal convulsive seizure detectors

Objective New devices are needed for monitoring seizures, especially those associated with sudden unexpected death in epilepsy (SUDEP). They must be unobtrusive and automated, and provide false alarm rates (FARs) bearable in everyday life. This study quantifies the performance of new multimodal wrist-worn convulsive seizure detectors. Methods Hand-annotated video-electroencephalographic seizure events were collected from 69 patients at six clinical sites. Three different wristbands were used to record electrodermal activity (EDA) and accelerometer (ACM) signals, obtaining 5,928 h of data, including 55 convulsive epileptic seizures (six focal tonic–clonic seizures and 49 focal to bilateral tonic–clonic seizures) from 22 patients. Recordings were analyzed offline to train and test two new machine learning classifiers and a published classifier based on EDA and ACM. Moreover, wristband data were analyzed to estimate seizure-motion duration and autonomic responses. Results The two novel classifiers consistently outperformed the previous detector. The most efficient (Classifier III) yielded sensitivity of 94.55%, and an FAR of 0.2 events/day. No nocturnal seizures were missed. Most patients had <1 false alarm every 4 days, with an FAR below their seizure frequency. When increasing the sensitivity to 100% (no missed seizures), the FAR is up to 13 times lower than with the previous detector. Furthermore, all detections occurred before the seizure ended, providing reasonable latency (median = 29.3 s, range = 14.8–151 s). Automatically estimated seizure durations were correlated with true durations, enabling reliable annotations. Finally, EDA measurements confirmed the presence of postictal autonomic dysfunction, exhibiting a significant rise in 73% of the convulsive seizures. Significance The proposed multimodal wrist-worn convulsive seizure detectors provide seizure counts that are more accurate than previous automated detectors and typical patient self-reports, while maintaining a tolerable FAR for ambulatory monitoring. Furthermore, the multimodal system provides an objective description of motor behavior and autonomic dysfunction, aimed at enriching seizure characterization, with potential utility for SUDEP warning

Review and Selection of Online Resources for Carers of Frail Adults or Older People in Five European Countries: Mixed-Methods Study

17.06.2020. BACKGROUND: Informal carers have a crucial role in the care of older people, but they are at risk of social isolation and psychological exhaustion. Web-based services like apps and websites are increasingly used to support informal carers in addressing some of their needs and tasks, such as health monitoring of their loved ones, information and communication, and stress management. Despite the growing number of available solutions, the lack of knowledge or skills of carers about the solutions often prevent their usage. OBJECTIVE: This study aimed to review and select apps and websites offering functionalities useful for informal carers of frail adults or older people in 5 European countries (Cyprus, Greece, Italy, Portugal, and Sweden). METHODS: A systematic online search was conducted from January 2017 to mid-March 2017 using selected keywords, followed by an assessment based on a set of commonly agreed criteria and standardized tools. Selected resources were rated and classified in terms of scope. Focus groups with informal carers were conducted to validate the list and the classification of resources. The activities were conducted in parallel in the participating countries using common protocols and guidelines, a standardization process, and scheduled group discussions. RESULTS: From a total of 406 eligible resources retrieved, 138 apps and 86 websites met the inclusion criteria. Half of the selected resources (109/224, 48.7%) were disease-specific, and the remaining resources included information and utilities on a variety of themes. Only 38 resources (38/224, 17.0%) were devoted specifically to carers, addressing the management of health disturbances and diseases of the care recipient and focusing primarily on neurodegenerative diseases. Focus groups with the carers showed that almost all participants had no previous knowledge of any resource specifically targeting carers, even if interest was expressed towards carer-focused resources. The main barriers for using the resources were low digital skills of the carers and reliability of health-related apps and websites. Results of the focus groups led to a new taxonomy of the resources, comprising 4 categories: carer's wellbeing, managing health and diseases of the care recipient, useful contacts, and technologies for eldercare. CONCLUSIONS: The review process allowed the identification of online resources of good quality. However, these resources are still scarce due to a lack of reliability and usability that prevent users from properly benefiting from most of the resources. The involvement of end users provided added value to the resource classification and highlighted the gap between the potential benefits from using information and communication technologies and the real use of online resources by carers.This study was co-funded by the Erasmus+ programme of the European Union, under the Project “Apps for carers”, Grant Agreement n. 2016-1-SE01-KA204-022067. This study was partially supported by Ricerca Corrente funding from the Italian Ministry of Health to IRCCS INRCA

The alteration of lipid metabolism in burkitt lymphoma identifies a novel marker: adipophilin

Background: Recent evidence suggests that lipid pathway is altered in many human tumours. In Burkitt lymphoma this is reflected by the presence of lipid droplets which are visible in the cytoplasm of neoplastic cells in cytological preparations. These vacuoles are not identifiable in biopsy section as lipids are "lost" during tissue processing. Methods and Results: In this study we investigated the expression of genes involved in lipid metabolism, at both RNA and protein level in Burkitt lymphoma and in other B-cell aggressive lymphoma cases. Gene expression profile indicated a significant over-expression of the adipophilin gene and marked up-regulation of other genes involved in lipid metabolism in Burkitt lymphoma. These findings were confirmed by immunohistochemistry on a series od additional histological samples: 45 out of 47 BL cases showed strong adipophilin expression, while only 3 cases of the 33 of the not-Burkitt lymphoma category showed weak adipophilin expression (p<0.05). Conclusions: Our preliminary results suggest that lipid metabolism is altered in BL, and this leads to the accumulation of lipid vacuoles. These vacuoles may be specifically recognized by a monoclonal antibody against adipophilin, which may therefore be a useful marker for Burkitt lymphoma because of its peculiar expression pattern. Moreover this peptide might represent an interesting candidate for interventional strategies. © 2012 Ambrosio et al

Multimodal wrist-worn devices for seizure detection and advancing research: Focus on the Empatica wristbands

Wearable automated seizure detection devices offer a high potential to improve seizure management, through continuous ambulatory monitoring, accurate seizure counts, and real-time alerts for prompt intervention. More importantly, these devices can be a life-saving help for people with a higher risk of sudden unexpected death in epilepsy (SUDEP), especially in case of generalized tonic-clonic seizures (GTCS). The Embrace and E4 wristbands (Empatica) are the first commercially available multimodal wristbands that were designed to sense the physiological hallmarks of ongoing GTCS: while Embrace only embeds a machine learning-based detection algorithm, both E4 and Embrace devices are equipped with motion (accelerometers, ACC) and electrodermal activity (EDA) sensors and both the devices received medical clearance (E4 from EU CE, Embrace from EU CE and US FDA). The aim of this contribution is to provide updated evidence of the effectiveness of GTCS detection and monitoring relying on the combination of ACM and EDA sensors. A machine learning algorithm able to recognize ACC and EDA signatures of GTCS-like events has been developed on E4 data, labeled using gold-standard video-EEG examined by epileptologists in clinical centers, and has undergone continuous improvement. While keeping an elevated sensitivity to GTCS (92–100%), algorithm improvements and growing data availability led to lower false alarm rate (FAR) from the initial ˜2 down to 0.2–1 false alarms per day, as showed by retrospective and prospective analyses in inpatient settings. Algorithm adjustment to better discriminate real-life physical activities from GTCS, has brought the initial FAR of ˜6 on outpatient real life settings, down to values comparable to best-case clinical settings (FAR < 0.5), with comparable sensitivity. Moreover, using multimodal sensing, it has been possible not only to detect GTCS but also to quantify seizure-induced autonomic dysfunction, based on automatic features of abnormal motion and EDA. The latter biosignal correlates with the duration of post-ictal generalized EEG suppression, a biomarker observed in 100% of monitored SUDEP cases. Keywords: Epilepsy; Convulsive seizures; Wearable device; SUDEP; Electrodermal activity; Machine learnin