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In this paper, we describe QUBIC, an experiment that will observe the polarized microwave sky with a novel approach, which combines the sensitivity of state-of-the-art bolometric detectors with the systematic effects control typical of interferometers. QUBIC’s unique features are the so-called “self-calibration”, a technique that allows us to clean the measured data from instrumental effects, and its spectral imaging power, i.e., the ability to separate the signal into various sub-bands within each frequency band. QUBIC will observe the sky in two main frequency bands: 150 GHz and 220 GHz. A technological demonstrator is currently under testing and will be deployed in Argentina during 2019, while the final instrument is expected to be installed during 2020.

In this paper, we describe QUBIC, an experiment that will observe the polarized microwave sky with a novel approach, which combines the sensitivity of state-of-the-art bolometric detectors with the systematic effects control typical of interferometers. QUBIC’s unique features are the so-called “self-calibration”, a technique that allows us to clean the measured data from instrumental effects, and its spectral imaging power, i.e., the ability to separate the signal into various sub-bands within each frequency band. QUBIC will observe the sky in two main frequency bands: 150 GHz and 220 GHz. A technological demonstrator is currently under testing and will be deployed in Argentina during 2019, while the final instrument is expected to be installed during 2020.

In this paper we describe QUBIC, an experiment that will observe the polarized microwave sky with a novel approach, which combines the sensitivity of state-of-the art bolometric detectors with the systematic effects control typical of interferometers. QUBIC unique features are the so-called \"self-calibration\", a technique that allows us to clean the measured data from instrumental effects, and its spectral imaging power, i.e. the ability to separate the signal in various sub-bands within each frequency band. QUBIC will observe the sky in two main frequency bands: 150 GHz and 220 GHz. A technological demonstrator is currently under testing and will be deployed in Argentina during 2019, while the final instrument is expected to be installed during 2020.

Malformations of cortical development (MCDs) are neurodevelopmental disorders that result from abnormal development of the cerebral cortex in utero. MCDs place a substantial burden on affected individuals, their families and societies worldwide, as these individuals can experience lifelong drug-resistant epilepsy, cerebral palsy, feeding difficulties, intellectual disability and other neurological and behavioural anomalies. The diagnostic pathway for MCDs is complex owing to wide variations in presentation and aetiology, thereby hampering timely and adequate management. In this article, the international MCD network Neuro-MIG provides consensus recommendations to aid both expert and non-expert clinicians in the diagnostic work-up of MCDs with the aim of improving patient management worldwide. We reviewed the literature on clinical presentation, aetiology and diagnostic approaches for the main MCD subtypes and collected data on current practices and recommendations from clinicians and diagnostic laboratories within Neuro-MIG. We reached consensus by 42 professionals from 20 countries, using expert discussions and a Delphi consensus process. We present a diagnostic workflow that can be applied to any individual with MCD and a comprehensive list of MCD-related genes with their associated phenotypes. The workflow is designed to maximize the diagnostic yield and increase the number of patients receiving personalized care and counselling on prognosis and recurrence risk.Malformations of cortical development (MCDs) are neurodevelopmental disorders that result from abnormal development of the cerebral cortex in utero. In this Consensus Statement, the international MCD network Neuro-MIG provides recommendations to aid both expert and non-expert clinicians in the diagnostic work-up of MCDs.

Background/Objectives: The Janus kinase inhibitors (JAKi) tofacitinib (TOFA), baricitinib (BARI), upadacitinib (UPA), and filgotinib (FILGO) are effective drugs for the treatment of rheumatoid arthritis. However, the US Food and Drug Administration (FDA) raised concerns about the safety of TOFA after its approval. This prompted the European Medicines Agency (EMA) to issue two safety warnings for limiting TOFA use, then extended a third warning to all JAKi in patients at high risk of developing serious adverse effects (SAE). These include thrombosis, major adverse cardiac events (MACE), and cancer. The purpose of this work was to analyze how the first two safety warnings from the EMA affected the prescribing of JAKi by rheumatologists in Italy. Methods: All patients with rheumatoid arthritis who had been prescribed JAKi for the first time in a 36-month period from 1 July 2019, to 30 June 2022 were considered. Data were obtained from the medical records of 29 Italian tertiary referral rheumatology centers. Patients were divided into three groups of 4 months each, depending on whether the JAKi prescription had occurred before the EMA’s first safety alert (1 July–31 October 2019, Group 1), between the first and second alerts (1 November 2019–29 February 2020, Group 2), or between the second and third alerts (1 March 2021–30 June 2021, Group 3). The percentages and absolute changes in the patients prescribed the individual JAKi were analyzed. Differences among the three groups of patients regarding demographic and clinical characteristics were also assessed. Results: A total of 864 patients were prescribed a JAKi during the entire period considered. Of these, 343 were identified in Group 1, 233 in Group 2, and 288 in Group 3. An absolute reduction of 32% was observed in the number of patients prescribed a JAKi between Group 1 and Group 2 and 16% between Group 1 and Group 3. In contrast, there was a 19% increase in the prescription of a JAKi in patients between Group 2 and Group 3. In the first group, BARI was the most prescribed drug (227 prescriptions, 66.2% of the total), followed by TOFA (115, 33.5%) and UPA (1, 0.3%). In the second group, the most prescribed JAKi was BARI (147, 63.1%), followed by TOFA (65, 27.9%) and UPA (33, 11.5%). In the third group, BARI was still the most prescribed JAKi (104 prescriptions, 36.1%), followed by UPA (89, 30.9%), FILGO (89, 21.5%), and TOFA (33, 11.5%). The number of patients prescribed TOFA decreased significantly between Group 1 and Group 2 and between Group 2 and Group 3 (p ˂ 0.01). The number of patients who were prescribed BARI decreased significantly between Group 1 and Group 2 and between Group 2 and Group 3 (p ˂ 0.01). In contrast, the number of patients prescribed UPA increased between Group 2 and Group 3 (p ˂ 0.01). Conclusions: These data suggest that the warnings issued for TOFA were followed by a reduction in total JAKi prescriptions. However, the more selective JAKi (UPA and FILGO) were perceived by prescribers as favorable in terms of the risk/benefit ratio, and their use gradually increased at the expense of the other molecules.

Bioresources need to be easily accessible to facilitate advancement of research. Besides technical and ethical aspects, a major obstacle for sharing them is the absence of recognition of the effort behind establishing and maintaining such resources.

Certain neuronal populations are selectively vulnerable to alpha-synuclein pathology in Parkinson's Disease, yet the reasons for this selectivity are unclear. Pathology affects neuronal populations that are anatomically connected although the contribution of neuronal connectivity remains to be quantitatively explored. Herein, we simulate the contribution of the connectome alone to the spread of arbitrary aggregates using a computational model of temporal spread within an abstract representation of the mouse mesoscale connectome. Our simulations are compared with the neuron-to-neuron spread of alpha-synuclein that has been observed with in vivo spreading experiments in rats. We find that neuronal connectivity appears to be compatible with the spreading pattern of alpha-synuclein pathology however, it may be per se insufficient to determine the anatomical pattern of protein spreading observed in experimental animals, suggesting a role of selective vulnerability of neuronal pathways to alpha-synuclein diffusion, accumulation and pathology. Footnotes * https://git.io/simulatedSpread