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Molecular determinants of protein pathogenicity at the single-aggregate level
Get PDFDetermining the structure-function relationships of protein aggregates is a fundamental challenge in biology. These aggregates, whether formed in vitro, within cells, or in living organisms, present significant heterogeneity in their molecular features such as size, structure, and composition, making it difficult to determine how their structure influences their functions. Interpreting how these molecular features translate into functional roles is crucial for understanding cellular homeostasis and the pathogenesis of various debilitating diseases like Alzheimer's and Parkinson's. In this study, we introduce a bottom-up approach to explore how variations in protein aggregates’ size, composition, post-translational modifications and point mutations profoundly influence their biological functions. Applying this method to Alzheimer's and Parkinson's associated proteins, we uncover the mechanism of novel disease-relevant pathways and demonstrate how subtle alterations in composition and morphology can shift the balance between healthy and pathological states. Our findings provide deeper insights into the molecular basis of protein’s functions at the single-aggregate level, enhancing our knowledge of their roles in health and disease
Enhancing Deployment-Time Predictive Model Robustness for Code Analysis and Optimization
Get PDFSupervised machine learning techniques have shown promising results in code analysis and optimization problems. However, a learning-based solution can be brittle because minor changes in hardware or application workloads – such as facing a new CPU architecture or code pattern – may jeopardize decision accuracy, ultimately undermining model robustness. We introduce Prom, an open-source library to enhance the robustness and performance of predictive models against such changes during deployment. Prom achieves this by using statistical assessments to identify test samples prone to mispredictions and using feedback on these samples to improve a deployed model. We showcase Prom by applying it to 13 representative machine learning models across 5 code analysis and optimization tasks. Our extensive evaluation demonstrates that Prom can successfully identify an average of 96% (up to 100%) of mispredictions. By relabeling up to 5% of the Prom-identified samples through incremental learning, Prom can help a deployed model achieve a performance comparable to that attained during its model training phase
Modelling, simulation, thermodynamic and economic performance analysis of steam and CO2 as diluents in thermal cracking furnace for ethylene manufacturing
No full textEnergy consumption, economic and environmental benefits of thermal cracking furnace have been important topics in ethylene manufacturing. Use of captured CO2 as alternative diluent in thermal cracking furnace can significantly contribute to CO2 reduction while the studies on CO2 as diluent are limited and inaccurate. To carry out comparative analysis of using steam and CO2 as diluents in propane cracking for ethylene manufacturing, a 1-dimensional (1-D) pseudo-dynamic model of plug flow reactor (PFR) was developed and implemented in gPROMS ModelBuilder®. The model was validated and showed good agreement with industrial data from literature and then was used to analyse the economic and thermodynamic performance of PFR using different diluents. The process analysis includes: (1) impact of diluent-to-propane ratio using steam as diluent; (2) impact of diluent-to-propane ratio using CO2 and compared with using steam; (3) comparison of pure/mixed diluents in 4 different scenarios. The results indicated that the PFR could reach highest annual production at the steam-to-propane ratio 0.2 and reach highest annual profit at the ratio 0.3 when using steam as diluent. Compared with steam, using CO2 as diluent hardly changes the annual production, but can significantly increase the run length and the annual profit. The highest annual profit using CO2 is 10.10 % higher than that using steam and when operating at the diluent-to-propane ratio achieving highest annual profit, using CO2 as diluent can save 17.44 % energy and reduce the exergy destruction by 20.53 %. Pure CO2 was recommended as diluent from comparison of pure/mixed diluents in 4 different scenarios. The key findings of this paper provide significant operational guidance for existing thermal cracking furnace using steam as diluent and also provide insights for future new generation diluents design to reduce the energy consumption in quantity and quality and increase the economic benefits of thermal cracking furnace for ethylene manufacturing
Topological and Morphological Membrane Dynamics in Giant Lipid Vesicles Driven by Monoolein Cubosomes
Get PDFLipid nanoparticles have important applications as biomedical delivery platforms and broader engineering biology applications in artificial cell technologies. These emerging technologies often require changes in the shape and topology of biological or biomimetic membranes. Here we show that topologically-active lyotropic liquid crystal nanoparticles (LCNPs) can trigger such transformations in the membranes of giant unilamellar vesicles (GUVs). Monoolein (MO) LCNPs, cubosomes with an internal nanostructure of space group mathematical equation incorporate into 1,2-dioleoyl-sn-glycero-3-phosphocholine (DOPC) GUVs creating excess membrane area with stored curvature stress. Using time-resolved fluorescence confocal and lattice light sheet microscopy, we observe and characterise various life-like dynamic events in these GUVs, including growth, division, tubulation, membrane budding and fusion. Our results shed new light on the interactions of LCNPs with bilayer lipid membranes, providing insights relevant to how these nanoparticles might interact with cellular membranes during drug delivery and highlighting their potential as minimal triggers of topological transitions in artificial cells
The Radio & Plasma Wave Investigation (RPWI) for the JUpiter ICy moons Explorer (JUICE)
Get PDFThe Radio & Plasma Wave Investigation (RPWI) onboard the ESA JUpiter ICy moons Explorer (JUICE) is described in detail. The RPWI provides an elaborate set of state-of-the-art electromagnetic fields and cold plasma instrumentation, including active sounding with the mutual impedance and Langmuir probe sweep techniques, where several different types of sensors will sample the thermal plasma properties, including electron and ion densities, electron temperature, plasma drift speed, the near DC electric fields, and electric and magnetic signals from various types of phenomena, e.g., radio and plasma waves, electrostatic acceleration structures, induction fields etc. A full wave vector, waveform, polarization, and Poynting flux determination will be achieved. RPWI will enable characterization of the Jovian radio emissions (including goniopolarimetry) up to 45 MHz, has the capability to carry out passive radio sounding of the ionospheric densities of icy moons and employ passive sub-surface radar measurements of the icy crust of these moons. RPWI can also detect micrometeorite impacts, estimate dust charging, monitor the spacecraft potential as well as the integrated EUV flux. The sensors consist of four 10 cm diameter Langmuir probes each mounted on the tip of 3 m long booms, a triaxial search coil magnetometer and a triaxial radio antenna system both mounted on the 10.6 m long MAG boom, each with radiation resistant pre-amplifiers near the sensors. There are three receiver boards, two Digital Processing Units (DPU) and two Low Voltage Power Supply (LVPS) boards in a box within a radiation vault at the centre of the JUICE spacecraft. Together, the integrated RPWI system can carry out an ambitious planetary science investigation in and around the Galilean icy moons and the Jovian space environment. Some of the most important science objectives and instrument capabilities are described here. RPWI focuses, apart from cold plasma studies, on the understanding of how, through electrodynamic and electromagnetic coupling, the momentum and energy transfer occur with the icy Galilean moons, their surfaces and salty conductive sub-surface oceans. The RPWI instrument is planned to be operational during most of the JUICE mission, during the cruise phase, in the Jovian magnetosphere, during the icy moon flybys, and in particular Ganymede orbit, and may deliver data from the near surface during the final crash orbit
Experimental analysis to quantify inactivation of microorganisms by Far-UVC irradiation in indoor environments
Get PDFFar-UVC irradiation at a 222 nm wavelength is a promising technology for inactivating microorganisms in indoor environments to mitigate transmission of infection. Here we report experimental measurements in a room-scale chamber to evaluate the performance of filtered Krypton-Chloride (KrCl) lamps in reducing the steady-state concentration of Staphylococcus aureus and Pseudomonas aeruginosa under different ventilation rates in indoor environments. The results showed a mean 95.5 % lowering of S. aureus load and 94.9 % of P. aeruginosa load at 3 air changes per hour (ACH) using one Far-UVC lamp and 97.8 % and >97.5 % using five lamps. At 1.5 ACH, the mean microbial reduction for S. aureus was >94.6 % and >99.5 % and at 9 ACH, it was 66.3 % and 91.9 % for 1 lamp and 5 lamps, respectively. Initial results at a shorter distance between the microbial source and collection sampling show a reduced but still substantial effect of the Far-UVC. The findings indicate that within these experimental conditions, Far-UVC can be effective at room-scale inactivation of a range of pathogens in a range of ventilation scenarios and also show promise at short-range inactivation. This research paves the way for future work to explore efficacy in real-world scenarios and to quantify usability and acceptability
Test-retest reliability of the Online Elicitation of Personal Utility Functions (OPUF) approach for valuing the EQ-HWB-S
Get PDFIntroduction
The EQ Health and Wellbeing Short (EQ-HWB-S) is a new 9-item instrument designed to generate utility values. However, its length makes traditional preference elicitation challenging. The Online elicitation of Personal Utility Functions (OPUF) approach has been tested as a potential solution. This study aimed to assess the test-retest reliability of OPUF for valuing the EQ-HWB-S.
Methods
The OPUF survey was administered twice, two weeks apart, to 220 German participants, including 73 from the general population and 147 patients with diabetes or rheumatic disease. Test-retest reliability was evaluated at individual and aggregate levels, examining dimension rankings, swing weights, level weights, and anchoring factors. Continuous data were analysed using the intraclass correlation coefficient (ICC), and ranking data were compared using Spearman’s correlation coefficient. Individual and aggregate level utility decrements were assessed using ICC and t-tests.
Results
Approximately 36% of participants had significantly correlated dimension ranks, with 42% selecting the same top-ranked dimension. Poor agreement was shown in 70% of ICC values for individual dimension swing weights. For intermediate level weights, ICC values showed poor agreement in 70% and moderate agreement in 30% of responses. The kappa for individual pairwise comparison tasks was 0.64 (95% CI: 0.54–0.75) showing moderate agreement; however, the ICC for individual-level anchoring factors was 0.12 (p < 0.05), indicating poor agreement. Aggregate utility decrements across dimensions were similar.
Conclusion
The OPUF approach generates reliable aggregate value sets for the EQ-HWB-S, but further exploration is needed to understand and address the reasons behind inconsistencies at the individual level
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