1,177 research outputs found

    Hereditary Sensory Neuropathy Type I secondary to SPTLC1/2 mutations: pathogenesis to treatment

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    Hereditary Sensory Neuropathy Type I (HSN1) secondary to SPTLC1/2 mutations is a rare, slowly progressive sensory-motor neuropathy, leading to profound sensory loss and variable, but often severe, motor deficits. The genes SPTLC1/2 encode for Serine Palmitoyltransferase, an essential enzyme in de-novo sphingolipid biosynthesis. SPTLC1/2 mutations alter its substrate specificity, leading to the synthesis and accumulation of atypical metabolites, 1-deoxysphinigolipids (1-deoxySLs). 1-DeoxySLs have been postulated to be neurotoxic however the underlying pathomechanism has not been elucidated. L-serine oral supplementation is a potential therapeutic candidate but the lack of responsive outcome measures is an obstacle in carrying out a definitive clinical trial. The first objective of this thesis was to determine if 1-deoxySLs are neurotoxic and to investigate the mechanism of their toxicity using two in-vitro neuronal models: 1) mouse primary motor and DRG neurons and 2) human iPSC derived sensory neurons. The second objective was to identify a responsive outcome measure by carrying out a natural history study. 1-deoxySL treatment resulted in dose dependent neurotoxicity in both in-vitro models. Findings in the mouse in-vitro model suggest mitochondrial and ER dysfunction as possible mediators of 1-deoxySL toxicity. Probing further into ER dysfunction using SH-SY5Y cells suggests 1-deoxySLs cause early ER stress leading to the activation of the unfolded protein response. In the HSN1 iPSC derived sensory neurons there was increased production of 1-deoxySLs and early cell loss but no functional or structural ER and mitochondrial defects in these neurons at 5 months. Assessments used in the natural history study included CMT Neuropathy score version 2, nerve conduction studies, quantitative sensory testing, computerised myometry, intra-epidermal nerve fibre density (thigh), MRI determined calf intramuscular fat accumulation, plasma 1-deoxySLs and patient based questionnaires. MRI determined calf muscle fat fraction showed validity and high responsiveness over 12 months and will be useful in HSN1 clinical trials

    Deep mutational scanning to understand the evolution of SARS-CoV-2 spike.

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    SARS-CoV-2 emerged as a zoonosis in 2019, causing a pandemic that led to significant global mortality, and devastating economic impact. SARS-CoV-2’s pathogenicity was related to its novelty in an immunologically naïve population. With increasing population immunity through vaccination and/or natural infection attenuating the disease, societies have been able to return to a semblance of normality, however SARS-CoV-2 has persisted to become endemic. With endemicity SARS-CoV-2 has continued to adapt and evolve, initially to optimise transmission and latterly to escape immune responses. To predict the future evolution, a deep mutagenesis scanning platform was developed. Deep mutagenesis scanning allows the phenotypic effects of thousands of mutations to be explored in a high-throughput manner. Using whole trimeric Alpha spike displayed on mammalian cells provided a physiologically relevant model and allowed the identification of mutations that increase ACE2 binding (the receptor for SARS-CoV-2 spike) and immune escape, which subsequently appeared in the Omicron lineages. Using this novel deep mutagenesis platform, the evolutionary trajectory of the SARS-CoV-2 receptor-binding domain can be seen to be restricted by epistasis. Vaccine induced immune responses against the receptor binding-domain are found to be remarkably focused on one or two residues despite being polyclonal and these residues have been repeatedly selected for in a variety of variants. From work exploring the antigenic effects of receptor-binding domain mutations, it becomes apparent the N-terminal domain contributes significantly to the immune escape seen with Delta and BA.1. This effect of the N-terminal domain does not appear to be mediated by escape from N-terminal domain directed antibodies, but by making the receptor-binding domain more difficult to neutralise. The plasticity of and focused immune response on the receptor-binding domain make further SARS-CoV-2 antigenic drift inevitable. Work described here suggests the most dramatic changes in antigenicity requires changes in both the N-terminal domain and receptor-binding domain.Open Acces

    Low-Power Mixed-Signal ASIC for Cryogenic SiPM Readout

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    L'abstract è presente nell'allegato / the abstract is in the attachmen

    Multiclass Alignment of Confidence and Certainty for Network Calibration

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    Deep neural networks (DNNs) have made great strides in pushing the state-of-the-art in several challenging domains. Recent studies reveal that they are prone to making overconfident predictions. This greatly reduces the overall trust in model predictions, especially in safety-critical applications. Early work in improving model calibration employs post-processing techniques which rely on limited parameters and require a hold-out set. Some recent train-time calibration methods, which involve all model parameters, can outperform the postprocessing methods. To this end, we propose a new train-time calibration method, which features a simple, plug-and-play auxiliary loss known as multi-class alignment of predictive mean confidence and predictive certainty (MACC). It is based on the observation that a model miscalibration is directly related to its predictive certainty, so a higher gap between the mean confidence and certainty amounts to a poor calibration both for in-distribution and out-of-distribution predictions. Armed with this insight, our proposed loss explicitly encourages a confident (or underconfident) model to also provide a low (or high) spread in the presoftmax distribution. Extensive experiments on ten challenging datasets, covering in-domain, out-domain, non-visual recognition and medical image classification scenarios, show that our method achieves state-of-the-art calibration performance for both in-domain and out-domain predictions. Our code and models will be publicly released.Comment: Accepted at GCPR 202

    Simulations of CMOS pixel sensors with a small collection electrode, improved for a faster charge collection and increased radiation tolerance

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    CMOS pixel sensors with a small collection electrode combine the advantages of a small sensor capacitance with the advantages of a fully monolithic design. The small sensor capacitance results in a large ratio of signal-to-noise and a low analogue power consumption, while the monolithic design reduces the material budget, cost and production effort. However, the low electric field in the pixel corners of such sensors results in an increased charge collection time, that makes a fully efficient operation after irradiation and a timing resolution in the order of nanoseconds challenging for pixel sizes larger than approximately forty micrometers. This paper presents the development of concepts of CMOS sensors with a small collection electrode to overcome these limitations, using three-dimensional Technology Computer Aided Design simulations. The studied design uses a 0.18 micrometer process implemented on a high-resistivity epitaxial layer.Comment: Proceedings of the PIXEL 2018 Worksho

    Exploring the Disproportionate Impact of COVID-19 in Older Adults in Canada

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    Background – Why are older Adults are Higher Risk? The majority of older adults have comorbid conditions, which are associated with a higher risk for COVID-19. Many live in residential care homes, which have seen the highest number of covid-19 cases due to tightly shared living spaces. With weakened immune systems, older adults living in poverty face additional challenges in protecting themselves from the virus, as it is difficult for them to comply with public health measures such as social distancing. 5% of individuals in the lowest income quartile were hospitalized due to covid19, compared to only 11.4% of individuals from the highest income quartile.   Methods – The data was retrieved from the Canadian MIS Database (CMDB) and the discharge abstract database (DAD). The CMDB contains financial and statistical operations information on public hospitals and regional health authorities across Canada. Case selection is based on COVID-19 diagnosis codes available in the International Statistical Classification of Diseases and Related Health Problems.   Results – Elderly faced higher rates of hospitalization during the pandemic. The average length of hospital stay was also higher for older adults—hospitalizations of individuals under age 65 without comorbidity 41,707 with comorbidity 12,372. Hospitalizations of individuals 65 and older without comorbidity were 22,221 with comorbidity 24,731. Higher Hospitalization rates and issues of inequality in the healthcare system globally. As the pandemic progressed, hospitalization increased in number significantly. The average length of stay for individuals younger than age 65 without comorbidity is 7.7 days compared to 17.0 days in patients with comorbidity. The average full length of stay for individuals 65 and older without comorbidity was 13.2 days, While in patients with comorbidity 19.2 days. Older adults had higher in-facility death rates due to COVID-19 hospitalization. The in-facility death rate of individuals younger than 65 without comorbidity is 2.5%, With comorbidity at 12.9%. In-facility death rate of individuals 65 and older without comorbidity is 14.4%, with comorbidity at 23.2%.   Conclusion – By analyzing and comparing various hospitalization rates for Canada, the precise data indicate that older adults have been disproportionatelyimpacted by COVID-19. It is now important to determine the underlying structural issues that have caused this inequality to prioritize healthy aging.   &nbsp
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