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Fast Möbius transform: an algebraic approach to information decomposition
No full textThe partial information decomposition (PID) and its extension integrated information decomposition (ΦID) are promising frameworks to investigate information phenomena involving multiple variables. An important limitation of these approaches is the high computational cost involved in their calculation. Here we leverage fundamental algebraic properties of these decompositions to enable a computationally-efficient method to estimate them, which we call the fast Möbius transform. Our approach is based on a formula for estimating the Möbius function that circumvents important computational bottlenecks and can in some cases offer a double-exponential speedup. We showcase the capabilities of this approach by presenting two analyses that would be unfeasible without this method: decomposing the information that neural activity at different frequency bands yields about the brain's macroscopic functional organization and identifying distinctive dynamical properties of the interactions between multiple voices in baroque music. Overall, our proposed approach illuminates the value of algebraic facets of information decomposition and opens the way to a wide range of future analyses
Learning Data-Driven Uncertainty Set Partitions for Robust and Adaptive Energy Forecasting with Missing Data
No full textNo effect of note order on the response of coal tits to conspecific, heterospecific and artificial mobbing calls
No full textMost Parid species produce specific, order-constrained mobbing calls. These calls elicit responses from both conspecifics and heterospecifics, with evidence indicating that such responses occur only when the calls are organised in this specific order. One notable exception is the coal tit (Periparus ater), a species that employs similar types of notes, yet does not exhibit clear order constraints within its mobbing sequences. Despite this apparent absence of order constraints, a recent experiment has demonstrated that coal tits may be sensitive to the order of notes in heterospecific calls. Therefore, the relative significance of note order in conspecific and heterospecific communication among coal tits remains unclear. We conducted a playback experiment to examine the effects of note order (natural coal tit order, typical Parid order and reversed order) and species identity (conspecific, familiar heterospecific-the great tit, Parus major, or artificial notes) on coal tit mobbing responses. Our findings indicate that coal tits exhibited a strong response to conspecific calls, regardless of the order of the notes; conversely, they displayed little to no response to heterospecific calls and artificial notes, irrespective of note order. A similar pattern was observed when assessing the general community response. This unexpectedly low response to familiar heterospecific calls may be attributable to a reduced density of great tits in the area we tested: ecological factors, such as community composition, may influence heterospecific mobbing behaviours and the subsequent biological interpretations of playback experiments. This study also underscores the necessity of conducting comparative research on closely related species to evaluate the potential generality of findings, such as strong order constraints recently observed in great tits and Japanese tits. This is an open access article under the terms of the Creative Commons Attribution License, which permits use, distribution and reproduction in any medium, provided the original work is properly cited
Research and development spending versus revenues after approval for CFTR modulators
No full textBackground: The high prices of CFTR modulators present barriers to access for people with cystic fibrosis (pwCF), especially those in low- and middle-income countries. Costs of research and development (R&D) are often cited as key drivers of drug pricing. In the case of CFTR modulators, circumstances allow for a meaningful comparison of pre-marketing R&D spending and post-approval product revenues.
Methods: Data on R&D expenditure and CFTR modulator revenues from Q3 2001 (the initial acquisition of CFTR modulator research) until 2024 were extracted from the originator company’s Securities and Exchange Commission filings. All values were inflation-adjusted to 2024. Cost of capital was incorporated at a discount rate of 10.5%, with rates of 7% and 14% modelled for sensitivity analysis.
Results: Total out-of-pocket R&D expenditure prior to the successful marketing of elexacaftor/tezacaftor/ivacaftor in Q3 2019 was 24.8 [13.2-41.6] billion. Actual costs associated with CFTR modulators are likely significantly lower than total R&D spending. Cumulative CFTR modulator revenues from 2012-24 were 63.8 billion, surpassing R&D expenditure in Q2 2020. At over 10.2 billion annually, elexacaftor/tezacaftor/ivacaftor represents one of the highest revenue pharmaceutical products currently on the market.
Conclusion: High revenues mean that R&D costs associated with CFTR modulators have been recouped early in their commercial lifespan. However, their pricing threatens global health equity for pwCF and the financial sustainability of health systems. In the eve of genetic therapies in CF and other rare diseases, sustainable solutions balancing equitable access and financial reward are urgently required
Exploring the influence of carbonaceous material on the photocatalytic performance of the composites containing Bi–BiOBr and P25 TiO2 for NOx remediation
No full textThe Bi–BiOBr–P25 TiO2 composite material exhibits high and synergistic improvements in the photocatalytic activity for nitrogen oxides (NOx = NO + NO2) removal. Herein, the influence of adding carbonaceous material to this composite, namely graphene (G), graphene oxide (GO), carbon nanotubes (CNT), and buckminsterfullerene (F) is explored; all at 1 wt%. Samples are synthesised using a one-pot solvothermal method. The structural and morphological properties, composition, and photocatalytic performance of all samples are examined using scanning electron microscopy, carbon–hydrogen–nitrogen elemental analysis, high-resolution transmission electron microscopy, X-ray diffraction, Raman spectroscopy, attenuated total reflectance–Fourier transform infrared spectroscopy, ultraviolet–visible (UV–vis) spectroscopy, X-ray photoelectron spectroscopy, N2 sorption at 77 K, photoluminescence spectroscopy, diffuse reflectance transient absorption spectroscopy), and photocatalytic testing against NOx gas in accordance with ISO protocol (22197-1:2016). Among the studied carbonaceous composites, the composite including GO shows the highest performance toward NOx remediation. For reactions in NO gas, it shows a combined higher NOx removal rate (21.9%) than its parent materials P25 (8.7%), Bi–BiOBr (6.5%), and GO (0%). For reactions in NO2 gas, it shows a higher NOx removal rate (≈15%) than its parent materials P25 (≈10%), Bi–BiOBr (≈5%), and GO (0%)
Exploring multidrug resistance patterns in community-acquired E. coli urinary tract infections with machine learning
No full textBackground
While associations of antibiotic resistance traits are not random in multidrug-resistant (MDR) bacteria, clinically relevant resistance patterns remain underexplored. This study used association-set mining to explore resistance associations within E. coli isolates from community-acquired urinary tract infection (UTI) isolates collected from 2018 to 2022 by France’s national surveillance system.
Methods
Association-set mining was applied separately to extended-spectrum beta-lactamase-producing E. coli (ESBL-EC) and non-ESBL-EC. MDR patterns with expected support (reflecting pattern frequency) and conditional lift (reflecting association strength) higher than expected by chance (p-value≤0.05) were used to construct resistance associations networks, and analysed according to time, age and gender.
Findings
The number of isolates increased from 360 287 in 2018 to 629 017 in 2022. More MDR patterns were selected in ESBL-EC than non-ESBL-EC (2022: 1770 vs 93 patterns), with higher respective network densities (2022: 0.301 vs 0.100). Fluoroquinolone, third-generation cephalosporin and penicillin resistances were strongly associated in ESBL-EC. Median networks densities increased from 2018 to 2022 in both ESBL-EC (0.238 to 0.301, p-value=0.06, Pearson test) and non-ESBL-EC (0.074 to 0.100, p-value=0.04). Across all years, median densities were higher in men than in women (ESBL-EC 2022: 0.305 vs 0.271; non-ESBL-EC: 0.128 vs 0.094), and higher in individuals over 65 than under 65 (ESBL-EC: 0.289 vs 0.275; non-ESBL-EC: 0.103 vs 0.088).
Interpretation
These findings highlight temporal, age-specific and gender-specific variations in resistance patterns, underscoring the potential of machine-learning to understand them and inform antibiotic strategies.
Funding
This work received funding from the National Research Agency project COMBINE ANR–22-PAMR-0003
Genetic control strategies for population suppression in the Anopheles gambiae complex: a review of current technologies
No full textMalaria continues to pose a critical public health threat, with mosquitoes from the Anopheles gambiae complex acting as the main vectors of the disease in sub-Saharan Africa, where approximately 95% of malaria-related deaths occur. Despite significant advancements in vector control, such as insecticide-treated bed nets and indoor spraying, the effectiveness of these interventions is increasingly compromised by various challenges, including rising levels of insecticide and pathogen resistance, mosquito behavioural adaptations, and persistent funding gaps. In this context, genetic vector control strategies have shown considerable promise, primarily based on findings from controlled laboratory studies. This review explores the development of these genetic approaches within the Anopheles gambiae complex and outlines future directions for their advancement and potential integration into malaria control efforts
Trigonometric gradient microstructures in additively manufactured single crystals enable strength-ductility synergy and programmable performance
No full textAdditively manufactured (AM) single crystals (SXs) show great promise for extreme-environment
applications. AM process enhances gradient microstructures around dendrites, including dislocation
densities, matrix channel width, precipitate area, and elemental concentrations. Here, we leverage a
unified trigonometric function describing all gradient microstructures in AM SXs, to quantify their
effects and enable programmable performance. We reveal that trigonometric gradient
microstructures (TGMs) can overcome strength-ductility trade-off, particularly at elevated
temperatures. In contrast, conventional gradient microstructures requiring post-treatment improve
strength at the expense of ductility. This benefit is attributed to the superposition relationship
between initial density-graded dislocations and other TGMs, rather than geometrically necessary
dislocations in conventional understanding. High-throughput simulations reveal linear correlations
between TGM intensity and mechanical properties. By mapping performance against TGMs, we can
tailor strength and elongation by tuning TGMs. This study deepens the understanding of gradient
microstructures around columnar dendrites in AM alloys and provides guidance for tailoring
mechanical properties
The effect of particle type and source material on microbial respiration on marine particles
No full textImperial Users onl
Identification of dual center in self-supported Pd-dispersed Cu2O/Cu nanowire arrays featuring cooperativity for durable electrochemical removal of low-concentration nitrate
No full textThis study fabricates a self-supported Pd-dispersed Cu2O/Cu nanowire array cathode through a facile galvanic replacement reaction. The hierarchical mesostructure of the electrode promotes enhanced mass transport and exhibits outstanding catalytic performance, achieving 98.7 % nitrate removal, 99.5 % N2 selectivity, and sustained stability over 40 cycles. Operando spectroscopic analysis identifies NO as a key intermediate, enabling the proposal of a consistent reaction pathway. Integrated experimental and theoretical studies reveal a synergistic mechanism in which stabilized Cu+ sites facilitate nitrate adsorption while Pd sites promote water dissociation to generate active hydrogen species (*H). Implemented in a continuous-flow electrochemical reactor with a two-electrode configuration, the system attains 81.1 % total nitrogen removal over 350 h at an energy consumption of 158.6 kWh·kg−1 N from a 35 mg·L−1 NO3--N feed solution, highlighting its potential for practical application. This work establishes an effective catalyst design strategy and provides a mechanistic foundation for energy-efficient nitrate purification