775 research outputs found

    Two emerging phenotypes of atypical inclusion body myositis: illustrative cases

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    OBJECTIVES: Sporadic inclusion body myositis (IBM) is the most common acquired myopathy in those aged above 50. It is classically heralded by weakness in the long finger flexors and quadriceps. The aim of this article is to describe five atypical cases of IBM, outlining two potential emerging clinical subsets of the disease. METHODS: We reviewed relevant clinical documentation and pertinent investigations for five patients with IBM. RESULTS: The first phenotype we describe is young-onset IBM in two patients who had symptoms since their early thirties. The literature supports that IBM can rarely present in this age range or younger. We describe a second phenotype in three middle-aged women who developed early bilateral facial weakness at presentation in tandem with dysphagia and bulbar impairment followed by respiratory failure requiring non-invasive ventilation (NIV). Within this group, two patients were noted to have macroglossia, another possible rare feature of IBM. CONCLUSIONS: Despite the classical phenotype described within the literature IBM can present in a heterogenous fashion. It is important to recognise IBM in younger patients and investigate for specific associations. The described pattern of facial diplegia, severe dysphagia, bulbar dysfunction and respiratory failure in female IBM patients requires further characterisation. Patients with this clinical pattern may require more complex and supportive management. Macroglossia is a potentially under recognised feature of IBM. The presence of macroglossia in IBM warrants further study, as its presence may lead to unnecessary investigations and delay diagnosis

    Encyclopedic VQA: Visual questions about detailed properties of fine-grained categories

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    We propose Encyclopedic-VQA, a large scale visual question answering (VQA) dataset featuring visual questions about detailed properties of fine-grained categories and instances. It contains 221k unique question+answer pairs each matched with (up to) 5 images, resulting in a total of 1M VQA samples. Moreover, our dataset comes with a controlled knowledge base derived from Wikipedia, marking the evidence to support each answer. Empirically, we show that our dataset poses a hard challenge for large vision+language models as they perform poorly on our dataset: PaLI [14] is state-of-the-art on OK-VQA [37], yet it only achieves 13.0% accuracy on our dataset. Moreover, we experimentally show that progress on answering our encyclopedic questions can be achieved by augmenting large models with a mechanism that retrieves relevant information from the knowledge base. An oracle experiment with perfect retrieval achieves 87.0% accuracy on the single-hop portion of our dataset, and an automatic retrieval-augmented prototype yields 48.8%. We believe that our dataset enables future research on retrieval-augmented vision+language models. It is available at https://github.com/google-research/google-research/tree/master/encyclopedic_vqa .Comment: ICCV'2

    A network analysis to compare biomarker profiles in patients with and without diabetes mellitus in acute heart failure

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    Aims: It is unclear whether distinct pathophysiological processes are present among patients with acute heart failure (AHF), with and without diabetes. Network analysis of biomarkers may identify correlative associations that reflect different pathophysiological pathways. Methods and results: We analysed a panel of 48 circulating biomarkers measured within 24 h of admission for AHF in a subset of patients enrolled in the PROTECT trial. In patients with and without diabetes, we performed a network analysis to identify correlations between measured biomarkers. Compared with patients without diabetes (n = 1111), those with diabetes (n = 922) had a higher prevalence of ischaemic heart disease and traditional coronary risk factors. After multivariable adjustment, patients with and without diabetes had significantly different levels of biomarkers across a spectrum of pathophysiological domains, including inflammation (TNFR-1a, periostin), cardiomyocyte stretch (BNP), angiogenesis (VEGFR, angiogenin), and renal function (NGAL, KIM-1) (adjusted P-value <0.05). Among patients with diabetes, network analysis revealed that periostin strongly clustered with C-reactive protein and interleukin-6. Furthermore, renal markers (creatinine and NGAL) closely associated with potassium and glucose. These findings were not seen among patients without diabetes. Conclusion: Patients with AHF and diabetes, compared with those without diabetes, have distinct biomarker profiles. Network analysis suggests that cardiac remodelling, inflammation, and fibrosis are closely associated with each other in patients with diabetes. Furthermore, potassium levels may be sensitive to changes in renal function as reflected by the strong renal–potassium–glucose correlation. These findings were not seen among patients without diabetes and may suggest distinct pathophysiological processes among AHF patients with diabetes

    Biomarker profiles of acute heart failure patients with a mid-range ejection fraction

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    OBJECTIVES: In this study, the authors used biomarker profiles to characterize differences between patients with acute heart failure with a midrange ejection fraction (HFmrEF) and compare them with patients with a reduced (heart failure with a reduced ejection fraction [HFrEF]) and preserved (heart failure with a preserved ejection fraction [HFpEF]) ejection fraction. BACKGROUND: Limited data are available on biomarker profiles in acute HFmrEF. METHODS: A panel of 37 biomarkers from different pathophysiological domains (e.g., myocardial stretch, inflammation, angiogenesis, oxidative stress, hematopoiesis) were measured at admission and after 24 h in 843 acute heart failure patients from the PROTECT trial. HFpEF was defined as left ventricular ejection fraction (LVEF) of ≄50% (n = 108), HFrEF as LVEF of <40% (n = 607), and HFmrEF as LVEF of 40% to 49% (n = 128). RESULTS: Hemoglobin and brain natriuretic peptide levels (300 pg/ml [HFpEF]; 397 pg/ml [HFmrEF]; 521 pg/ml [HFrEF]; ptrend <0.001) showed an upward trend with decreasing LVEF. Network analysis showed that in HFrEF interactions between biomarkers were mostly related to cardiac stretch, whereas in HFpEF, biomarker interactions were mostly related to inflammation. In HFmrEF, biomarker interactions were both related to inflammation and cardiac stretch. In HFpEF and HFmrEF (but not in HFrEF), remodeling markers at admission and changes in levels of inflammatory markers across the first 24 h were predictive for all-cause mortality and rehospitalization at 60 days (pinteraction <0.05). CONCLUSIONS: Biomarker profiles in patients with acute HFrEF were mainly related to cardiac stretch and in HFpEF related to inflammation. Patients with HFmrEF showed an intermediate biomarker profile with biomarker interactions between both cardiac stretch and inflammation markers. (PROTECT-1: A Study of the Selective A1 Adenosine Receptor Antagonist KW-3902 for Patients Hospitalized With Acute HF and Volume Overload to Assess Treatment Effect on Congestion and Renal Function; NCT00328692)

    Serum potassium levels and outcome in acute heart failure (data from the PROTECT and COACH trials)

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    Serum potassium is routinely measured at admission for acute heart failure (AHF), but information on association with clinical variables and prognosis is limited. Potassium measurements at admission were available in 1,867 patients with AHF in the original cohort of 2,033 patients included in the Patients Hospitalized with acute heart failure and Volume Overload to Assess Treatment Effect on Congestion and Renal FuncTion trial. Patients were grouped according to low potassium (<3.5 mEq/l), normal potassium (3.5 to 5.0 mEq/l), and high potassium (>5.0 mEq/l) levels. Results were verified in a validation cohort of 1,023 patients. Mean age of patients was 71 – 11 years, and 66% were men. Low potassium was present in 115 patients (6%), normal potassium in 1,576 (84%), and high potassium in 176 (9%). Potassium levels increased during hospitalization (0.18 – 0.69 mEq/l). Patients with high potassium more often used angiotensin-converting enzyme inhibitors and mineralocorticoid receptor antagonists before admission, had impaired baseline renal function and a better diuretic response (p [ 0.005), independent of mineralocorticoid receptor antagonist usage. During 180-day follow-up, a total of 330 patients (18%) died. Potassium levels at admission showed a univariate linear association with mortality (hazard ratio [log] 2.36, 95% confidence interval 1.07 to 5.23; p [ 0.034) but not after multivariate adjustment. Changes of potassium levels during hospitalization or potassium levels at discharge were not associated with outcome after multivariate analysis. Results in the validation cohort were similar to the index cohort. In conclusion, high potassium levels at admission are associated with an impaired renal function but a better diuretic response. Changes in potassium levels are common, and overall levels increase during hospitalization. In conclusion, potassium levels at admission or its change during hospitalization are not associated with mortality after multivariate adjustment

    Catalyst Journal of the Amateur Yacht Research Society

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    CATALYST is a journal of yacht research, design and technology published by the Amateur Yacht Research Society, BCM AYRS, London, WC1N 3XX, UK 3. Innov-Sail – 29 to 31 May 2023 by John Perry 8 Regional NWLG Windemere meeting - 6th June 2023ncrease of subscription from September 2023 10 Balanced Foils, Part 2, by Ian Ward 29 Artificial Intelligence by Richard Fish 35 Howard Fund revisited : The Winners and the Losers By Mike Howar

    Multiscale digital Arabidopsis predicts individual organ and whole-organism growth

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    Understanding how dynamic molecular networks affect wholeorganism physiology, analogous to mapping genotype to phenotype, remains a key challenge in biology. Quantitative models that represent processes at multiple scales and link understanding from several research domains can help to tackle this problem. Such integrated models are more common in crop science and ecophysiology than in the research communities that elucidate molecular networks. Several laboratories have modeled particular aspects of growth in Arabidopsis thaliana, but it was unclear whether these existing models could productively be combined. We test this approach by constructing a multiscale model of Arabidopsis rosette growth. Four existing models were integrated with minimal parameter modification (leaf water content and one flowering parameter used measured data). The resulting framework model links genetic regulation and biochemical dynamics to events at the organ and whole-plant levels, helping to understand the combined effects of endogenous and environmental regulators on Arabidopsis growth. The framework model was validated and tested with metabolic, physiological, and biomass data from two laboratories, for five photoperiods, three accessions, and a transgenic line, highlighting the plasticity of plant growth strategies. The model was extended to include stochastic development. Model simulations gave insight into the developmental control of leaf production and provided a quantitative explanation for the pleiotropic developmental phenotype caused by overexpression of miR156, which was an open question. Modular, multiscale models, assembling knowledge from systems biology to ecophysiology, will help to understand and to engineer plant behavior from the genome to the field. (Résumé d'auteur

    The predictive validity of a Brain Care Score for dementia and stroke: data from the UK Biobank cohort

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    Introduction: The 21-point Brain Care Score (BCS) was developed through a modified Delphi process in partnership with practitioners and patients to promote behavior changes and lifestyle choices in order to sustainably reduce the risk of dementia and stroke. We aimed to assess the associations of the BCS with risk of incident dementia and stroke. Methods: The BCS was derived from the United Kingdom Biobank (UKB) baseline evaluation for participants aged 40–69 years, recruited between 2006–2010. Associations of BCS and risk of subsequent incident dementia and stroke were estimated using Cox proportional hazard regressions, adjusted for sex assigned at birth and stratified by age groups at baseline. Results: The BCS (median: 12; IQR:11–14) was derived for 398,990 UKB participants (mean age: 57; females: 54%). There were 5,354 incident cases of dementia and 7,259 incident cases of stroke recorded during a median follow-up of 12.5 years. A five-point higher BCS at baseline was associated with a 59% (95%CI: 40-72%) lower risk of dementia among participants aged 59 years. A five-point higher BCS was associated with a 48% (95%CI: 39-56%) lower risk of stroke among participants aged 59. Discussion: The BCS has clinically relevant and statistically significant associations with risk of dementia and stroke in approximately 0.4 million UK people. Future research includes investigating the feasibility, adaptability and implementation of the BCS for patients and providers worldwide
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