47 research outputs found

    COVID-19 symptoms at hospital admission vary with age and sex: results from the ISARIC prospective multinational observational study

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    Background: The ISARIC prospective multinational observational study is the largest cohort of hospitalized patients with COVID-19. We present relationships of age, sex, and nationality to presenting symptoms. Methods: International, prospective observational study of 60 109 hospitalized symptomatic patients with laboratory-confirmed COVID-19 recruited from 43 countries between 30 January and 3 August 2020. Logistic regression was performed to evaluate relationships of age and sex to published COVID-19 case definitions and the most commonly reported symptoms. Results: ‘Typical’ symptoms of fever (69%), cough (68%) and shortness of breath (66%) were the most commonly reported. 92% of patients experienced at least one of these. Prevalence of typical symptoms was greatest in 30- to 60-year-olds (respectively 80, 79, 69%; at least one 95%). They were reported less frequently in children (≀ 18 years: 69, 48, 23; 85%), older adults (≄ 70 years: 61, 62, 65; 90%), and women (66, 66, 64; 90%; vs. men 71, 70, 67; 93%, each P < 0.001). The most common atypical presentations under 60 years of age were nausea and vomiting and abdominal pain, and over 60 years was confusion. Regression models showed significant differences in symptoms with sex, age and country. Interpretation: This international collaboration has allowed us to report reliable symptom data from the largest cohort of patients admitted to hospital with COVID-19. Adults over 60 and children admitted to hospital with COVID-19 are less likely to present with typical symptoms. Nausea and vomiting are common atypical presentations under 30 years. Confusion is a frequent atypical presentation of COVID-19 in adults over 60 years. Women are less likely to experience typical symptoms than men

    HuR modulates gemcitabine efficacy: new perspectives in pancreatic cancer treatment.

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    EVALUATION OF: Costantino CL, Witkiewicz AK, Kuwano Y et al. The role of HuR in gemcitabine efficacy in pancreatic cancer: HuR up-regulates the expression of the gemcitabine metabolizing enzyme deoxycytidine kinase. Cancer Res. 69, 4567-4572 (2009). Gemcitabine has been the standard of care for pancreatic cancer for a decade but is only effective in some patients. As a prodrug, gemcitabine is activated by different protein kinases. The deoxycytidine kinase (dCK) is the first step of intracellular activation. We review the study by Costantino and colleagues, evaluating the consequence of modulating Hu antigen R (HuR), a stress response protein, on dCK expression and the correlation between HuR expression levels and pancreatic cancer outcome. This study demonstrates that dCK protein concentration levels were regulated by HuR and that a high cytoplasmic HuR level was associated with a sevenfold decreased risk of mortality after resection of pancreatic adenocarcinoma and gemcitabine therapy.Journal Articleinfo:eu-repo/semantics/publishe

    Direct digital synthesiser (DDS) design parameters optimisation for vibrating MEMS sensors: Optimisation of phase accumulator, Look-Up Table (LUT) and Digital to Analog Converter (DAC) sizes

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    International audienceOnera has been developing quartz based MEMS inertial sensors for long, including for some years the associated digital electronics. Direct Digital Synthesis (DDS) and computerised control loops have been introduced as a replacement for self-sustained oscillators and analog PLL. However, the design parameters of digital synthesisers (word length of phase accumulator, size of Look Up Table, number of bits of DAC) affect the excitation signal spectrum driving the sensors. Spurious noise induced by those parameters can alter the sensors performances, especially in our cases of highly resonant vibrating structures (Q > 100000): spurs close to the resonant frequency tend to lower the quality factor. This paper exposes a review of this spurious noise and an approach for optimising the DDS design parameters. In addition, alternate DDS structures are also investigated and compared to the classical phase accumulator / look up table / D-A converter structure. In one case, the DAC is only one bit wide, and the sine shape is obtained through large oversampling and low-pass filtering (Σ/Δ technique). In space designs, the ability to skip the DAC and remain fully digital inside a FPGA is a trade-off to be considered. In an other case, the output is only a square but with low jitter, reshaped by a narrow band pass filter, to generate the expected sine output. Here, the trade-off is towards simpler electronics (no memory table) with a slightly more sophisticated analog filter

    Accurate Frequency Counting Architecture for Vibrating Accelerometers on FPGA

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    International audienceOnera has developed a quartz based Vibrating Beam Accelerometer (VBA) with frequency output. A new digital electronics architecture is introduced, which matches the accelerometer performances. To do so, the new architecture must detect a 3 10−10 relative frequency shift after 10 s of measurement. Experiments made assert the developed electronics reach such performances

    Thermal profile construction for energy-intensive industrial sectors

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    Industrial plant data are difficult to find in academic literature for a number of reasons such as confiden- tiality, and thus intentional masking, or problem size reduction. These common practices limit the ability of researchers to apply novel methods to real cases and understand energy consumption of real industrial plant instances. This is especially pertinent in the field of process integration, as realistic representations of real processes form the basis for the application of novel technologies. Few efforts have been made in this area [1, 2] demonstrating the added value of these profiles; thus, a clear methodology is required for constructing such energy consumption profiles. The method proposed in this work defines an approach for constructing the heat profiles of major industries in a generic way. Parameterized models of several major European industries are presented for defining specific production/plant instances based on contextual specificities to represent different production pathways. The profile construction methodology is described for several situations of data access. Confidentiality issues are addressed by different anonymization techniques such as aggregation, sta- tistical treatment, or by using data which are already publicly available. In this work, data were gathered from real plant operations and validated at higher levels using public information. Although the potential applications and implications of these profiles are clear, two cases are presented to exhibit adaptation of the parameterized models to specific instances and profile use for process integration problems. Varying the model parameters represents different plant instances and thus yield different integration solutions for the major process industries included in this work
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