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Artificial intelligence-powered automatic coronary computed tomography angiography plaque quantification: comparison against optical coherence tomography
Get PDFAims: Coronary computed tomography angiography (CCTA) enables a non-invasive, comprehensive assessment of coronary artery disease, and artificial intelligence (AI) offers the potential to improve CCTA image interpretation. This study aimed to evaluate the performance of an AI-powered method for automatic plaque quantification from CCTA, with optical coherence tomography (OCT) as reference standard. Methods and results: Patients who underwent CCTA within 6 months prior to OCT were retrospectively enrolled. AI-assisted automatic plaque quantification was performed on CCTA with specific plaque composition classification based on adaptive Hounsfield unit thresholds. Qualitative high-risk plaque features were also assessed. Automated co-registration of CCTA and OCT was performed with the link of invasive coronary angiography. A total of 91 patients with 153 co-registered lesions were evaluated. The AI-assisted automatic CCTA analysis showed significant correlations with OCT for quantifying plaque volume/burden and different plaque compositions (all P values 0.33 on OCT, was identified in 39 (25.5%) lesions. CCTA-derived plaque volume >82.5 mm3 [odds ratio (OR), 9.39], maximal plaque burden >76.4% (OR, 3.70), lipidic tissue volume >16.3 mm³ (OR, 4.42), all P < 0.001, and high-risk plaque features ≥2 (OR, 2.70, P = 0.009) were independent predictors of OCT-derived vulnerable plaques. The average time for automatic CCTA plaque quantification was 1.8 min per patient. Conclusion: The novel AI-powered method facilitated fully automatic plaque quantification and correlated well with co-registered OCT
HCR-Proxy resolves site-specific proximal RNA microenvironments at subcompartmental resolution
Get PDFThe spatial organization of RNA-scaffolded condensates is fundamental for understanding of basic cellular functions, but may also provide pivotal insights into diseases. One of the major challenges to understanding the role of condensates is the lack of technologies to map condensate-scale protein architecture at subcompartmental resolution. To address this, we introduce HCR-Proxy, a proximity labelling technique that couples hybridization chain reaction (HCR)-based signal amplification with in situ proximity biotinylation (Proxy), enabling proteomic profiling of RNA-proximal proteomes at subcompartmental resolution. We applied HCR-Proxy to nascent pre-rRNA targets to investigate the distinct proteomic signatures of the nucleolar subcompartments and to uncover a spatial logic of protein partitioning shaped by RNA sequence. Our results demonstrate the ability of HCR-Proxy to provide spatially resolved maps of RNA interactomes within the nucleolus, offering new insights into the molecular organization and compartmentalization of condensates. This subcompartment-specific nucleolar proteome profiling enabled integration with deep learning frameworks, which effectively confirmed a sequence-encoded basis for protein partitioning across nested condensate subcompartments, characterized by antagonistic gradients in charge, molecular weight, and RNA-binding domains. HCR-Proxy thus provides a scalable platform for spatially resolved RNA interactome discovery, bridging transcript localization with proteomic context in native cellular environments
Interface storage of vanadium based materials in zinc-ion batteries
Get PDFIn the study of aqueous zinc-ion batteries, vanadium-based materials, as typical insertion-type cathode materials, present an inherent contradiction in simultaneously achieving high energy density (deep-level insertion) and high power density (fast kinetics), a phenomenon referred to as the “Ragone conflict”. While constructing artificial interfaces has been shown to enhance both capacity and kinetics, the underlying mechanisms of these improvements primarily rely on qualitative understanding. In this brief focus article, we elucidate the interface storage model of vanadium-based materials, providing a more quantitative approach to describing interface kinetics and specific capacity. In some reports involving vanadium-based heterostructures, there is evidence suggesting that zinc storage may rely on interfacial storage in specific materials, accompanied by reversible interfacial bond rearrangement (interfacial breathing) and decoupled ionic/electronic transport (job-sharing), thereby achieving more and faster zinc ion storage, providing an effective solution to the Ragone conflict
The art of judgement: thinking and writing in sixteenth-century France
No full textThe art of judgement did not reside in a single codified theory. Rather, it was a shared preoccupation with the practice, limits, and possibilities of how to master the methods and ideals of rhetoric and dialectic that shaped early modern thought. This thesis explores the art of judgement, from the pedagogical writings of Erasmus, Agricola, Latomus, and Ramus, to its varied enactment in the works of Jean Bodin, Étienne Pasquier, and Michel de Montaigne. Part I reconstructs the pedagogical culture in which judgement was cultivated, showing how rhetorical and dialectical precepts were animated by a language of judgement that sought to grasp the very moments where rules and methods falter. One of the contentions of this thesis is that judgement was used to attend to the limits and edges of early modern discursive theory and practice—where literary abundance exceeds its bounds, where imitation strains against precedent, and where the commonplace method meets the act of intellectual agency. Part II moves from theory to practice, showing how Bodin, Pasquier, and Montaigne inherited and extended the ways of thinking and writing with judgement. Each of these writers framed and conceptualised their own intellectual practice using the language of judgement. Judgement emerges in different forms, from grasping logical order to the expression of one’s character. For Bodin, Pasquier, and Montaigne, judgement is the instrument that gathers together the centrifugal abundance of Renaissance learning into a centripetal art of making sense. By placing these three writers together, this thesis is able to use the art of judgement as a critical framework to explore both the family resemblances and the radical differences between their works. Understanding the uses of, and preoccupation with, judgement allows this thesis to recast the structure of sixteenth century thought
Strategic incentives and regulation in cyber security
Get PDFThis thesis studies the optimal design of policy in the domains of data protection and cyber security. Each of the three main chapters consists of an independent paper. The first paper studies a digital platform’s incentives to invest in protecting the consumer data it collects. Data security investment is unobserved by consumers and incentives are reputational. In a two-period model, I show that a planner can raise total consumer welfare by imposing ex-ante limits on data collection based on a firm’s history of data breaches. The optimal policy depends on whether firms or consumers control data collection in each period. Additionally, I use the model to evaluate established policies: minimum security standards and limits to data retention. The second paper studies how markets for ransomware insurance affect the welfare of firms and hackers, and asks whether regulation can improve outcomes. In the model, hackers may or may not observe victims’ insurance contracts, and firms may be unable to pay ransom due to liquidity constraints. Insurance has commitment value for the firms in their bargaining with hackers and can reduce ransom demands. Regulatory caps on insurance for ransom payments guarantee that the presence of insurers makes firms better off, and hackers worse off. The third paper focuses on a fundamental trade-off that regulators face when designing data-breach notification laws: high penalties following disclosure encourage firms to invest in cybersecurity ex-ante but also to conceal breaches ex-post. In the model, a firm only discloses a breach after it has become pessimistic about the prospect of concealing it. I characterize the optimal policy for a regulator who can commit to penalties following disclosure of a breach. I examine design of the optimal policy when disclosure delay is ex-post verifiable and the regulator uses delay-dependent penalties to screen firms' private information
Investigating the influence of radio-faint active galactic nuclei on the infrared-radio correlation of massive galaxies
Get PDFContext.
It is well known that star-forming galaxies (SFGs) exhibit a tight correlation between their radio and infrared emissions, commonly referred to as the infrared-radio correlation (IRRC). Recent empirical studies have reported a dependence of the IRRC on the galaxy stellar mass, in which more massive galaxies tend to show lower infrared-to-radio ratios (
q
IR
) with respect to less massive galaxies. One possible, yet unexplored, explanation is a residual contamination of the radio emission from active galactic nuclei (AGNs), not captured through “radio-excess” diagnostics.
Aims.
To investigate this hypothesis, we aim to statistically quantify the contribution of AGN emission to the radio luminosities of SFGs located within the scatter of the IRRC.
Methods.
Our Very Large Baseline Array (VLBA) AGN-sCAN program has targeted 500 galaxies that follow the
q
IR
distribution of the IRRC, i.e., with no prior evidence for radio-excess AGN emission based on low-resolution (∼arcsec) VLA radio imaging. Our VLBA 1.4 GHz observations reach a 5
σ
sensitivity limit of 25 μJy/beam, corresponding to a radio-brightness temperature of
T
b
∼ 10
5
K. This classification serves as a robust AGN diagnostic, regardless of the host galaxy’s star formation rate.
Results.
We detect four VLBA sources in the deepest regions, which are also the faintest VLBI-detected AGNs in SFGs to date. The effective AGN detection rate is 9%, when considering a control sample matched in mass and sensitivity, which is in good agreement with the extrapolation of previous radio AGN number counts. Despite the non-negligible AGN flux contamination (∼30%) in our individual VLBA detections, we find that the peak of the
q
IR
distribution is completely unaffected by this correction. Although we cannot rule out a high incidence of radio-silent AGNs at (sub)μJy levels among the VLBA non-detections, we derive a conservative upper limit of < 0.1 dex of their cumulative impact on the
q
IR
distribution. We conclude that residual AGN contamination from non-radio-excess AGNs is unlikely to be the primary driver of the
M
★
– dependent IRRC
The alpha rhythm: from physiology to behaviour
Get PDFThe alpha rhythm, first identified by Hans Berger 100 years ago, is the dominant non-invasive electrophysiological signature of the healthy human brain in the awake state. For decades, it was believed that the alpha rhythm reflected rest or idling; however, this perspective changed in the 2000s when researchers found that alpha oscillations increase with cognitive demands. This discovery led to a paradigm shift, demonstrating that alpha oscillations reflect the functional inhibition of brain regions that are not needed for a specific task, thereby directing information to task-specific areas. We have reviewed the physiological mechanisms involved in generating alpha oscillations, which has informed computational models explaining how these oscillations emerge within physiologically realistic networks. At the behavioural level, alpha oscillations are strongly modulated across nearly all cognitive paradigms tested in humans, reflecting the allocation of computational resources within the active brain network. Research in individuals with attention-related issues has highlighted their impaired ability to modulate alpha oscillations, which is associated with performance deficits. Therefore, further exploration of alpha oscillations has the potential to uncover causal mechanisms underlying attention problems, such as those related to ADHD and ageing. Lastly, advancements in technology are opening new avenues for characterising alpha oscillations in ecologically valid settings and across the lifespan. This progress sets the stage for exploring the role of alpha oscillations in cognitive development and their functioning in natural environments
Figure data: A statistical theory of electronic degrees of freedom in wave packet molecular dynamics
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Report of a one-day convening on regulatory science, practices, and innovative approaches to facilitate approval of novel combination vaccines
Get PDFCombination vaccine formulations contain distinct components targeting multiple strains of a single pathogen or multiple pathogens. By minimizing the number of separate vaccine administrations required, combination vaccines have been critical in allowing the broad expansion of the number and range of diseases that can now be prevented by immunization. Recent advances in vaccine development and our understanding of the immune system now make it possible to envision how new combination vaccines could play a major role in helping immunization programs address a much wider range of emerging or still problematic pathogens. However, few combinations are currently in the pipeline, in part due to their inherently increased complexity and cost of development compared to standalone formulations. This complexity, in turn, is partly driven by the regulatory requirements surrounding the clinical study program for the combination vaccine, especially the primary clinical endpoints and the required degree of precision around those endpoints, as these ultimately determine the sample size, cost, and duration of the study. As part of a larger effort to facilitate combination vaccine development, vaccine experts at the World Health Organization and PATH coordinated a one-day meeting in March 2025 gathering current and former national regulatory agency staff from a dozen countries, together with vaccine developers, representatives from funding and procurement agencies, and public health and policy officials. The convened participants held spirited discussions on how multiple immune markers and controlled human infection models (CHIM) might contribute to the demonstration of vaccine efficacy. In addition, participants considered the possibility of relying on clinical endpoints when the vaccine components are directed against pathogens causing the same disease syndrome but etiological determination of each component's contribution is not feasible. Regulators welcomed scientifically sound, creative proposals for demonstration of efficacy, and agreed that the benefit-risk of the combination vaccine as a whole should be the primary focus