1,258 research outputs found

    Delayed Cryptochrome Degradation Asymmetrically Alters the Daily Rhythm in Suprachiasmatic Clock Neuron Excitability.

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    Suprachiasmatic nuclei (SCN) neurons contain an intracellular molecular circadian clock and the Cryptochromes (CRY1/2), key transcriptional repressors of this molecular apparatus, are subject to post-translational modification through ubiquitination and targeting for proteosomal degradation by the ubiquitin E3 ligase complex. Loss-of-function point mutations in a component of this ligase complex, Fbxl3, delay CRY1/2 degradation, reduce circadian rhythm strength, and lengthen the circadian period by ∼2.5 h. The molecular clock drives circadian changes in the membrane properties of SCN neurons, but it is unclear how alterations in CRY1/2 stability affect SCN neurophysiology. Here we use male and femaleAfterhoursmice which carry the circadian period lengthening loss-of-functionFbxl3Afhmutation and perform patch-clamp recordings from SCN brain slices across the projected day/night cycle. We find that the daily rhythm in membrane excitability in the ventral SCN (vSCN) was enhanced in amplitude and delayed in timing inFbxl3Afh/Afhmice. At night, vSCN cells fromFbxl3Afh/Afhmice were more hyperpolarized, receiving more GABAergic input than theirFbxl3+/+counterparts. Unexpectedly, the progression to daytime hyperexcited states was slowed byAfhmutation, whereas the decline to hypoexcited states was accelerated. In long-term bioluminescence recordings, GABAAreceptor blockade desynchronized theFbxl3+/+but not theFbxl3Afh/AfhvSCN neuronal network. Further, a neurochemical mimic of the light input pathway evoked larger shifts in molecular clock rhythms inFbxl3Afh/Afhcompared withFbxl3+/+SCN slices. These results reveal unanticipated consequences of delaying CRY degradation, indicating that theAfhmutation prolongs nighttime hyperpolarized states of vSCN cells through increased GABAergic synaptic transmission.SIGNIFICANCE STATEMENTThe intracellular molecular clock drives changes in SCN neuronal excitability, but it is unclear how mutations affecting post-translational modification of molecular clock proteins influence the temporal expression of SCN neuronal state or intercellular communication within the SCN network. Here we show for the first time, that a mutation that prolongs the stability of key components of the intracellular clock, the cryptochrome proteins, unexpectedly increases in the expression of hypoexcited neuronal state in the ventral SCN at night and enhances hyperpolarization of ventral SCN neurons at this time. This is accompanied by increased GABAergic signaling and by enhanced responsiveness to a neurochemical mimic of the light input pathway to the SCN. Therefore, post-translational modification shapes SCN neuronal state and network properties

    Cost-Effectiveness of Pediatric Central Venous Catheters in the UK: A Secondary Publication from the CATCH Clinical Trial

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    Background: Antibiotic-impregnated central venous catheters (CVCs) reduce the risk of bloodstream infections (BSIs) in patients treated in pediatric intensive care units (PICUs). However, it is unclear if they are cost-effective from the perspective of the National Health Service (NHS) in the UK. Methods: Economic evaluation alongside the CATCH trial (ISRCTN34884569) to estimate the incremental cost effectiveness ratio (ICER) of antibiotic-impregnated (rifampicin and minocycline), heparin-bonded and standard polyurethane CVCs. The 6-month costs of CVCs and hospital admissions and visits were determined from administrative hospital data and case report forms. Results: BSIs were detected in 3.59% (18/502) of patients randomized to standard, 1.44% (7/486) to antibiotic and 3.42% (17/497) to heparin CVCs. Lengths of hospital stay did not differ between intervention groups. Total mean costs (95% confidence interval) were: £45,663 (£41,647–£50,009) for antibiotic, £42,065 (£38,322–£46,110) for heparin, and £44,503 (£40,619–£48,666) for standard CVCs. As heparin CVCs were not clinically effective at reducing BSI rate compared to standard CVCs, they were considered not to be cost-effective. The ICER for antibiotic vs. standard CVCs, of £54,057 per BSI avoided, was sensitive to the analytical time horizon. Conclusions: Substituting standard CVCs for antibiotic CVCs in PICUs will result in reduced occurrence of BSI but there is uncertainty as to whether this would be a cost-effective strategy for the NH

    Grout rheological properties for preplaced aggregate concrete production

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    yesThis paper investigates the effect of cement based grout rheology on the injection process through coarse aggregate for producing preplaced aggregate concrete. Four different sands were used in the grout production at different water-cement ratios and cement-sand ratios. Superplasticiers and pulverised fuel ash were also employed in the grout production. Coarse aggregate of known weight was compacted into 150 mm cubic forms, and then the grout was injected through a plastic pipe under self weight into the stone ‘skeleton’. It has been found that there are threshold values of the rheological parameters beyond which full injection is not possible. In particular, all grout mixes with and without additives and admixtures exhibited the same yield stress threshold value for full injection, whereas the threshold values for other rheological properties including the grout plastic viscosity, flow time and speed were different according to the materials added to the mix

    Validation and Clinical Applicability of Whole-Volume Automated Segmentation of Optical Coherence Tomography in Retinal Disease Using Deep Learning.

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    IMPORTANCE: Quantitative volumetric measures of retinal disease in optical coherence tomography (OCT) scans are infeasible to perform owing to the time required for manual grading. Expert-level deep learning systems for automatic OCT segmentation have recently been developed. However, the potential clinical applicability of these systems is largely unknown. OBJECTIVE: To evaluate a deep learning model for whole-volume segmentation of 4 clinically important pathological features and assess clinical applicability. DESIGN, SETTING, AND PARTICIPANTS: This diagnostic study used OCT data from 173 patients with a total of 15 558 B-scans, treated at Moorfields Eye Hospital. The data set included 2 common OCT devices and 2 macular conditions: wet age-related macular degeneration (107 scans) and diabetic macular edema (66 scans), covering the full range of severity, and from 3 points during treatment. Two expert graders performed pixel-level segmentations of intraretinal fluid, subretinal fluid, subretinal hyperreflective material, and pigment epithelial detachment, including all B-scans in each OCT volume, taking as long as 50 hours per scan. Quantitative evaluation of whole-volume model segmentations was performed. Qualitative evaluation of clinical applicability by 3 retinal experts was also conducted. Data were collected from June 1, 2012, to January 31, 2017, for set 1 and from January 1 to December 31, 2017, for set 2; graded between November 2018 and January 2020; and analyzed from February 2020 to November 2020. MAIN OUTCOMES AND MEASURES: Rating and stack ranking for clinical applicability by retinal specialists, model-grader agreement for voxelwise segmentations, and total volume evaluated using Dice similarity coefficients, Bland-Altman plots, and intraclass correlation coefficients. RESULTS: Among the 173 patients included in the analysis (92 [53%] women), qualitative assessment found that automated whole-volume segmentation ranked better than or comparable to at least 1 expert grader in 127 scans (73%; 95% CI, 66%-79%). A neutral or positive rating was given to 135 model segmentations (78%; 95% CI, 71%-84%) and 309 expert gradings (2 per scan) (89%; 95% CI, 86%-92%). The model was rated neutrally or positively in 86% to 92% of diabetic macular edema scans and 53% to 87% of age-related macular degeneration scans. Intraclass correlations ranged from 0.33 (95% CI, 0.08-0.96) to 0.96 (95% CI, 0.90-0.99). Dice similarity coefficients ranged from 0.43 (95% CI, 0.29-0.66) to 0.78 (95% CI, 0.57-0.85). CONCLUSIONS AND RELEVANCE: This deep learning-based segmentation tool provided clinically useful measures of retinal disease that would otherwise be infeasible to obtain. Qualitative evaluation was additionally important to reveal clinical applicability for both care management and research

    How different are the British in their willingness to move? Evidence from International Social Survey Data

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    Our paper analyses people's willingness to move (WTM) using data from the 1995 British Social Attitudes Survey and International Social Survey Programme. We identify the personal characteristics and sub-regional indicators that are important in explaining the WTM within Britain. We also find that the WTM is only higher in a few other countries, including the United States. The equivalent desire to move is found to be much lower in Eastern European countries and in several other European Union member states. Compositional effects, such as age and education, are generally important in explaining differences in attitudes towards migration in comparison to other Western economies. However, structural effects such as institutions, history and culture tend to play a more dominant role in explaining differences compared to countries in Central and Eastern Europe

    A Toy Model for Testing Finite Element Methods to Simulate Extreme-Mass-Ratio Binary Systems

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    Extreme mass ratio binary systems, binaries involving stellar mass objects orbiting massive black holes, are considered to be a primary source of gravitational radiation to be detected by the space-based interferometer LISA. The numerical modelling of these binary systems is extremely challenging because the scales involved expand over several orders of magnitude. One needs to handle large wavelength scales comparable to the size of the massive black hole and, at the same time, to resolve the scales in the vicinity of the small companion where radiation reaction effects play a crucial role. Adaptive finite element methods, in which quantitative control of errors is achieved automatically by finite element mesh adaptivity based on posteriori error estimation, are a natural choice that has great potential for achieving the high level of adaptivity required in these simulations. To demonstrate this, we present the results of simulations of a toy model, consisting of a point-like source orbiting a black hole under the action of a scalar gravitational field.Comment: 29 pages, 37 figures. RevTeX 4.0. Minor changes to match the published versio

    Automated analysis of retinal imaging using machine learning techniques for computer vision

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    There are almost two million people in the United Kingdom living with sight loss, including around 360,000 people who are registered as blind or partially sighted. Sight threatening diseases, such as diabetic retinopathy and age related macular degeneration have contributed to the 40% increase in outpatient attendances in the last decade but are amenable to early detection and monitoring. With early and appropriate intervention, blindness may be prevented in many cases. Ophthalmic imaging provides a way to diagnose and objectively assess the progression of a number of pathologies including neovascular (“wet”) age-related macular degeneration (wet AMD) and diabetic retinopathy. Two methods of imaging are commonly used: digital photographs of the fundus (the ‘back’ of the eye) and Optical Coherence Tomography (OCT, a modality that uses light waves in a similar way to how ultrasound uses sound waves). Changes in population demographics and expectations and the changing pattern of chronic diseases creates a rising demand for such imaging. Meanwhile, interrogation of such images is time consuming, costly, and prone to human error. The application of novel analysis methods may provide a solution to these challenges. This research will focus on applying novel machine learning algorithms to automatic analysis of both digital fundus photographs and OCT in Moorfields Eye Hospital NHS Foundation Trust patients. Through analysis of the images used in ophthalmology, along with relevant clinical and demographic information, Google DeepMind Health will investigate the feasibility of automated grading of digital fundus photographs and OCT and provide novel quantitative measures for specific disease features and for monitoring the therapeutic success

    Comparative evaluation of structured oil systems : shellac oleogel, HPMC oleogel, and HIPE gel

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    In lipid-based food products, fat crystals are used as building blocks for creating a crystalline network that can trap liquid oil into a 3D gel-like structure which in turn is responsible for the desirable mouth feel and texture properties of the food products. However, the recent ban on the use of trans-fat in the US, coupled with the increasing concerns about the negative health effects of saturated fat consumption, has resulted in an increased interest in the area of identifying alternative ways of structuring edible oils using non-fat-based building blocks. In this paper, we give a brief account of three alternative approaches where oil structuring was carried out using wax crystals (shellac), polymer strands (hydrophilic cellulose derivative), and emulsion droplets as structurants. These building blocks resulted in three different types of oleogels that showed distinct rheological properties and temperature functionalities. The three approaches are compared in terms of the preparation process (ease of processing), properties of the formed systems (microstructure, rheological gel strength, temperature response, effect of water incorporation, and thixotropic recovery), functionality, and associated limitations of the structured systems. The comparative evaluation is made such that the new researchers starting their work in the area of oil structuring can use this discussion as a general guideline
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