Digital Catapult

Hepatocellular carcinoma (HCC) is a leading cause of cancer-related mortality worldwide, with incidence and mortality projected to rise. Most patients present with advanced or unresectable disease, where treatment efficacy is often constrained by frailty and impaired physical function. As physical function has emerged as a key determinant of treatment eligibility and survival, there is growing interest in physical activity as a supportive intervention in HCC care. This narrative review synthesises observational, pre-clinical, and trial evidence on the role of physical activity in patients with HCC, examining its potential to improve treatment tolerance, quality of life, and survival. A literature search was conducted across four databases (PubMed, Scopus, Web of Science, Embase) using keywords related to HCC, physical activity, exercise, and survivorship. Pre-clinical studies reveal multiple mechanisms through which physical activity may enhance anti-tumour responses, including metabolic reprogramming, modulation of oncogenic signalling and immune activation. Observational studies suggest that frailty and sarcopenia - markers of reduced physical function, are possibly associated with early treatment discontinuation and shorter survival in HCC. Preliminary interventional data suggest that structured exercise programmes, delivered in hospital, outpatient, telehealth, or mobile formats, can improve frailty, preserve muscle mass, and may potentially support survival. However, clinical studies to date are limited by small sample sizes, non-randomised designs, and short follow-up periods. Current evidence provides a biologically plausible and clinically promising rationale for integrating physical activity into HCC care pathways. While findings are encouraging, robust randomised trials are needed to establish efficacy, define optimal exercise regimens, and evaluate long-term outcomes.

Studies of the early visual system often require characterizing the visual preferences of large populations of neurons. This task typically requires multiple stimuli such as sparse noise and drifting gratings, each of which probes only a limited set of visual features. Here, we introduce a new dynamic stimulus with sharp-edged stripes that we term Zebra noise and a new analysis model based on wavelets, and we show that in combination they are highly efficient for mapping multiple aspects of the visual preferences of thousands of neurons. We used two-photon calcium imaging to record the activity of neurons in the mouse visual cortex. Zebra noise elicited strong responses that were more repeatable than those evoked by traditional stimuli. The wavelet-based model captured the repeatable aspects of the resulting responses, providing measures of neuronal tuning for multiple stimulus features: position, orientation, size, spatial frequency, drift rate, and direction. The method proved efficient, requiring only 5 minutes of stimulus (repeated three times) to characterize the tuning of thousands of neurons across visual areas. In combination, the Zebra noise stimulus and the wavelet-based model provide a broadly applicable toolkit for the rapid characterization of visual representations, promising to accelerate future studies of visual function.

Optical coherence tomography (OCT) is a state-of-the art imaging technique which has revolutionized high-resolution medical imaging. Despite its widespread adoption, the inherent trade-off between imaging range and speed of OCT remains a significant challenge. This is particularly true for applications in ophthalmology, where the incessant movement of the eye demands a high imaging speed, whilst the highly-curved surfaces of the retina and cornea require a long detection range. We present a novel method of controlling the imaging depth via opto-electronic phase modulation of the reference arm. Our hybrid approach combines off-the-shelf components and numerical reconstruction. We showcase an eight-fold effective axial range extension at a 400 kHz A-scan rate. Using a fast phase modulation scheme in lieu of a conventional mechanical delay line allowed us to adjust the imaging depth on a per-A-scan basis. This ensures that the surface of interest remains within the axial range, which is limited by the high A-scan rate, even in the presence of significant variations in surface contour. By compensating for the surface shape during acquisition, our approach ensures a high data throughput and avoids the speed-range trade-off. Harmonic OCT can be readily integrated into commercial systems. This can expand the field-of-view of high-speed clinical OCT imaging.

X-ray Diffraction Computed Tomography (XRD-CT) represents a cutting-edge method for non-destructive material analysis, offering the unique capability of providing molecular-level information with spatial resolution. In this study, we have applied XRD-CT to investigate pharmaceutically relevant tablets that have been subjected to a range of compression pressures typical in tablet manufacturing. By employing XRD-CT to pharmaceutical tablets, we reveal material changes without tablet destruction, thereby avoiding potential phase transformations during sample preparation that could lead to errors in the interpretation of the processes that have occurred. Utilizing a pressure-sensitive marker, glycolide, we have tracked changes within tablet structures induced by compression, pinpointing locations where glycolide undergoes pressure-induced transformation. Additionally, we conducted a follow-up study with analysis one month later, observing an in situ hydrolysis reaction of glycolide within the tablets. Through the complementary use of electron diffraction, we have elucidated the structure of the hydrolysis product, further enhancing our understanding of temporal changes in the tablets.

This paper describes the 6th Affective Behavior Analysis in-the-wild (ABAW) Competition, which is part of the respective Workshop held in conjunction with IEEE CVPR 2024. The 6th ABAW Competition addresses contemporary challenges in understanding human emotions and behaviors, crucial for the development of human-centered technologies. In more detail, the Competition focuses on affect related benchmarking tasks and comprises of five subchallenges: i) Valence-Arousal Estimation (the target is to estimate two continuous affect dimensions, valence and arousal), ii) Expression Recognition (the target is to recognise between the mutually exclusive classes of the 7 basic expressions and 'other'), iii) Action Unit Detection (the target is to detect 12 action units), iv) Compound Expression Recognition (the target is to recognise between the 7 mutually exclusive compound expression classes), and v) Emotional Mimicry Intensity Estimation (the target is to estimate six continuous emotion dimensions). In the paper, we present these Challenges, describe their respective datasets and challenge protocols (we outline the evaluation metrics) and present the baseline systems as well as their obtained performance. More information for the Competition can be found in: https://affective-behavioranalysis-in-the-wild.github.io/6th.

Amidst the dominance of virtual era, the vast use of screens and smartphones has led to a worrisome increase in global reliance on digital sources. World Digital Detox Day has arisen as an essential endeavor in response to the urgent necessity to cope with this depend. The principal goal is to foster a worldwide motion in the direction of achieving a kingdom of healthy balance and attention in our digital life. The article offers a succinct summary of the primary desires, processes, and predicted results of this challenge. The motive of this endeavor is to enhance awareness regarding the adverse effects related to prolonged screen exposure and virtual engagement. Stakeholders from diverse sectors, together with generation, healthcare, training, and policymaking, will collaborate to deal with this count number. The primary goal of this initiative is to enable people to reclaim authority over their virtual lifestyles through the promotion of more advantageous digital behaviors, the cultivation of virtual literacy, and the establishment of environments that facilitate virtual cleansing. The objective of World Digital Detox Day is to foster a sustainable and harmonious connection with generation via centered interventions and network engagement. This will usefully resource in mitigating the negative influences of overdependence on virtual gadgets on each non-public welfare and societal dynamics.

Nature Outlines are supplements to Nature, supported by external funding. They use infographics and animation to make complex scientific concepts accessible. Nature has sole responsibility for all editorial content (see go.nature.com/33m79fz).

Federated learning (FL) systems face performance challenges in dealing with heterogeneous devices and non-identically distributed data across clients. We propose a dynamic global model aggregation method within Asynchronous Federated Learning (AFL) deployments to address these issues. Our aggregation method scores and adjusts the weighting of client model updates based on their upload frequency to accommodate differences in device capabilities. Additionally, we also immediately provide an updated global model to clients after they upload their local models to reduce idle time and improve training efficiency. We evaluate our approach within an AFL deployment consisting of 10 simulated clients with heterogeneous compute constraints and non-IID data. The simulation results, using the Fashion-MNIST dataset, demonstrate over 10% and 19% improvement in global model accuracy compared to state-of-the-art methods PAPAYA and FedAsync, respectively. Our dynamic aggregation method allows reliable global model training despite limiting client resources and statistical data heterogeneity. This improves robustness and scalability for real-world FL deployments.