the congenital disorders of glycosylation community perspective

BACKGROUND: Congenital disorders of glycosylation (CDG) are a large family of rare genetic diseases for which therapies are virtually nonexistent. However, CDG therapeutic research has been expanding, thanks to the continuous efforts of the CDG medical/scientific and patient communities. Hence, CDG drug development is a popular research topic. The main aim of this study was to understand current and steer future CDG drug development and approval by collecting and analysing the views and experiences of the CDG community, encompassing professionals and families. An electronic (e-)survey was developed and distributed to achieve this goal. RESULTS: A total of 128 respondents (46 CDG professionals and 82 family members), mainly from Europe and the USA, participated in this study. Most professionals (95.0%) were relatively familiar with drug development and approval processes, while CDG families revealed low familiarity levels, with 8.5% admitting to never having heard about drug development. However, both stakeholder groups agreed that patients and families make significant contributions to drug development and approval. Regarding their perceptions of and experiences with specific drug development and approval tools, namely biobanks, disease models, patient registries, natural history studies (NHS) and clinical trials (CT), the CDG community stakeholders described low use and participation, as well as variable familiarity. Additionally, CDG professionals and families shared conflicting views about CT patient engagement and related information sharing. Families reported lower levels of involvement in CT design (25.0% declared ever being involved) and information (60.0% stated having been informed) compared to professionals (60.0% and 85.7%, respectively). These contrasting perceptions were further extended to their insights and experiences with patient-centric research. Finally, the CDG community (67.4% of professionals and 54.0% of families) reported a positive vision of artificial intelligence (AI) as a drug development tool. Nevertheless, despite the high AI awareness among CDG families (76.8%), professionals described limited AI use in their research (23.9%). CONCLUSIONS: This community-centric study sheds new light on CDG drug development and approval. It identifies educational, communication and research gaps and opportunities for CDG professionals and families that could improve and accelerate CDG therapy development.publishersversionpublishe

Testing long range beam-beam compensation for the LHC luminosity upgrade

The performance of the Large Hadron Collider (LHC) at CERN and its minimum crossing angle are limited by long-range beam-beam collisions. A wire compensators can mitigate part of the long-range effects and may allow for smaller crossing angles, or higher beam intensity. A prototype long-range wire compensator should be installed in the LHC by 2014/15. The originally reserved position for the wire compensator (named BBC) seems not available in this first step, we need so to test other possibilities. The performed tests consider various longitudinal and transverse locations, different wire shapes, different optics configuration and trying several crossing angles between the beam. Simulation are done with the weak-strong code BBtrack developed by U. Dorda. New postprocessing tools were used to analyse tune footprints and particle stability In particular for particle stability was implemented a new method for the Lyapunov coefficient calculation

Simulation studies for the LHC long-range beam-beam compensators

The performance of the Large Hadron Collider (LHC) and its minimum crossing angle are limited by long-range beam-beam collisions. Wire compensators can mitigate part of the long-range effects and may allow for smaller crossing angles, smaller β*, or higher beam intensity. A prototype long-range wire compensator should be installed in the LHC by 2014/15. We report simulation studies examining and comparing the efficiency of the wire compensation, in terms of tune footprint or dynamic aperture, at various candidate locations, with different wire shapes, and for varying transverse distance from the beam

Design of low-impact impedances devices: the new proton synchrotron booster absorber scraper (PSBAS)

At CERN the HL-LHC (High Luminosity Large Hadron Collider) and the LIU (LHC Injection Upgrade) projects call for an increase in beam parameters such as energy, intensityand brightness. To achieve this goal the whole accelerator complex will be upgraded. Systems, equipment and devices need to be redesigned and rebuilt accounting for the demanding new beam features. In this framework device impedance is a key parameter. It is essential to evaluate and to minimize the impedance of the component during its early design phase. This avoids beam instabilities and minimizes beam losses and induced heating. In this paper we outline general guidelines for a low-impedance design and we show how to implement them in a real case, taking as example the design of the new Proton Synchrotron Booster Absorber Scraper (PSBAS). This is a key component aimed to remove the beam halo at the beginning of the LHC accelerator chain

Artificial intelligence in epigenetic studies: shedding light on rare diseases

More than 7,000 rare diseases (RDs) exist worldwide, affecting approximately 350 million people, out of which only 5% have treatment. The development of novel genome sequencing techniques has accelerated the discovery and diagnosis in RDs. However, most patients remain undiagnosed. Epigenetics has emerged as a promise for diagnosis and therapies in common disorders (e.g., cancer) with several epimarkers and epidrugs already approved and used in clinical practice. Hence, it may also become an opportunity to uncover new disease mechanisms and therapeutic targets in RDs. In this "big data" age, the amount of information generated, collected, and managed in (bio)medicine is increasing, leading to the need for its rapid and efficient collection, analysis, and characterization. Artificial intelligence (AI), particularly deep learning, is already being successfully applied to analyze genomic information in basic research, diagnosis, and drug discovery and is gaining momentum in the epigenetic field. The application of deep learning to epigenomic studies in RDs could significantly boost discovery and therapy development. This review aims to collect and summarize the application of AI tools in the epigenomic field of RDs. The lower number of studies found, specific for RDs, indicate that this is a field open to expansion, following the results obtained for other more common disorders.info:eu-repo/semantics/publishedVersio

MD1787 - LHC TDI tune shift measurement at injection

This report summarizes the results of the backup activity performed after cancellation of the MD1787. This MD was originally conceived to measure the instability growth rate versus chromaticity and damper settings at injections energy in the LHC, but, due to an RFQ issue in the Linac2 followed by an issue with the LHC cryogenic system, the original plan could not be executed. As a short backup activity on the available time given by the daylight saving on 30th October 2016 and the kind cooperation with other LHC MD users, it was decided to characterize with beam the TDI impedance

Machine Development Studies in the CERN PS Booster, in 2016

The paper presents the outstanding studies performed in 2016 in preparation of the PS Booster upgrade, within the LHC Injector Upgrade project (LIU), to provide twice higher brightness and intensity to the High-Luminosity LHC. Major changes include the increase of injection and extraction energy, the implementation of a H⁻ charge-exchange injection system, the replacement of the present Main Power Supply and the deployment of a new RF system (and related Low-Level), based on the Finemet technology. Although the major improvements will be visible only after the upgrade, the present machine can already benefit of the work done, in terms of better brightness, transmission and improved reproducibility of the present operational beams. Studies address the space-charge limitations at low energy, for which a detailed optics model is needed and for which mitigation measurements are under study, and the blow-up reduction at injection in the downstream machine, for which the beams need careful preparation and transmission. Moreover they address the requirements and the reliability of new beam instrumentation and hardware that is being installed in view of LIU

Building the impedance model of a real machine

International audienceA reliable impedance model of a particle accelerator can be built by combining the beam coupling impedances of all the components. This is a necessary step to be able to evaluate the machine performance limitations, identify the main contributors in case an impedance reduction is required, and study the interaction with other mechanisms such as optics nonlinearities, transverse damper, noise, space charge, electron cloud, beam-beam (in a collider). The main phases to create a realistic impedance model, and verify it experimentally, will be reviewed, highlighting the main challenges. Some examples will be presented revealing the levels of precision of machine impedance models that have been achieved